DEPARTMENT OF HEALTH AND HUMAN SERVICES

Centers for Medicare & Medicaid Services

42 CFR Part 412

[CMS-1627-P]

RIN 0938-AS47

Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System - Update 

for Fiscal Year Beginning October 1, 2015 (FY 2016)

AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION: Proposed rule.

SUMMARY: This proposed rule would update the prospective payment rates for

Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs) (which are 

freestanding IPFs and psychiatric units of an acute care hospital or critical access hospital). 

These changes would be applicable to IPF discharges occurring during the fiscal year (FY) 

beginning October 1, 2015 through September 30, 2016 (FY 2016). This proposed rule also 

proposes: a new IPF-specific market basket; to update the IPF labor-related share; a transition to

new Core Based Statistical Area (CBSA) designations in the FY 2016 IPF Prospective Payment 

System (PPS) wage index; to phase out the rural adjustment for IPF providers whose status 

changes from rural to urban as a result of the proposed wage index CBSA changes; and new

quality measures and reporting requirements under the IPF quality reporting program. This 

proposed rule also reminds IPFs of the October 1, 2015 implementation of the International 

Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), and updates

providers on the status of IPF PPS refinements.

DATES: To be assured consideration, comments must be received at one of the addresses 
CMS-1627-P 2

provided below, no later than 5 p.m. on June 23, 2015.

ADDRESSES: In commenting, please refer to file code CMS-1627-P. Because of staff and 

resource limitations, we cannot accept comments by facsimile (FAX) transmission.

You may submit comments in one of four ways (please choose only one of the ways 

listed):

1. Electronically. You may submit electronic comments on this regulation to 

http://www.regulations.gov. Follow the "Submit a comment" instructions.

2. By regular mail. You may mail written comments to the following address ONLY:

Centers for Medicare & Medicaid Services,

Department of Health and Human Services,

Attention: CMS-1627-P,

P.O. Box 8010,

Baltimore, MD 21244-1850.

Please allow sufficient time for mailed comments to be received before the close of the 

comment period.

3. By express or overnight mail. You may send written comments to the following 

address ONLY:

Centers for Medicare & Medicaid Services,

Department of Health and Human Services,

Attention: CMS-1627-P,

Mail Stop C4-26-05,

7500 Security Boulevard,

Baltimore, MD 21244-1850.
CMS-1627-P 3

4. By hand or courier. Alternatively, you may deliver (by hand or courier) your 

written comments ONLY to the following addresses prior to the close of the comment period:

a. For delivery in Washington, DC--

Centers for Medicare & Medicaid Services,

Department of Health and Human Services,

Room 445-G, Hubert H. Humphrey Building,

200 Independence Avenue, SW.,

Washington, DC 20201

(Because access to the interior of the Hubert H. Humphrey Building is not readily 

available to persons without Federal government identification, commenters are encouraged to 

leave their comments in the CMS drop slots located in the main lobby of the building. A stampin clock is available for persons wishing to retain a proof of filing by stamping in and retaining 

an extra copy of the comments being filed.) 

b. For delivery in Baltimore, MD--

Centers for Medicare & Medicaid Services,

Department of Health and Human Services,

7500 Security Boulevard,

Baltimore, MD 21244-1850. 

If you intend to deliver your comments to the Baltimore address, call telephone number 

(410) 786-4492 in advance to schedule your arrival with one of our staff members.

Comments erroneously mailed to the addresses indicated as appropriate for hand or 

courier delivery may be delayed and received after the comment period.
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For information on viewing public comments, see the beginning of the 

"SUPPLEMENTARY INFORMATION" section.

FOR FURTHER INFORMATION CONTACT:

Katherine Lucas or Jana Lindquist, (410) 786-7723, for general information.

Hudson Osgood, (410) 786-7897 or Bridget Dickensheets, (410) 786-8670, for information 

regarding the market basket and labor-related share.

Theresa Bean, (410) 786-2287, for information regarding the regulatory impact analysis.

Rebecca Kliman, (410) 786-9723, or Jeffrey Buck, (410)786-0407, for information regarding the 

inpatient psychiatric facility quality reporting program. 

SUPPLEMENTARY INFORMATION:

Availability of Certain Tables Exclusively Through the Internet on the CMS Website

In the past, tables setting forth the Wage Index for Urban Areas Based on CBSA Labor 

Market Areas and the Wage Index Based on CBSA Labor Market Areas for Rural Areas were 

published in the Federal Register as an Addendum to the annual PPS rulemaking (that is, the 

PPS proposed and final rules or, when applicable, the current update notice). However, 

beginning in FY 2015, these wage index tables are no longer published in the Federal Register. 

Instead, these tables will be available exclusively through the Internet. The wage index tables 

for this proposed rule are available exclusively through the Internet on the CMS website at

http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.

To assist readers in referencing sections contained in this document, we are providing the 

following table of contents.

I. Executive Summary

A. Purpose
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B. Summary of the Major Provisions

C. Summary of Impacts

II. Background

A. Overview of the Legislative Requirements of the IPF PPS

B. Overview of the IPF PPS

C. Annual Requirements for Updating the IPF PPS

III. Provisions of the Proposed Rule

A. Proposed Market Basket for the IPF PPS 

1. Background

2. Overview of the Proposed 2012-Based IPF Market Basket

3. Creating an IPF-specific Market Basket

a. Development of Cost Categories and Weights

i. Medicare Cost Reports 

ii. Final Major Cost Category Computation

iii. Derivation of the Detailed Operating Cost Weights

iv. Derivation of the Detailed Capital Cost Weights

v. Proposed 2012-based IPF Market Basket Cost Categories and Weights

b. Selection of Price Proxies

i. Price Proxies for the Operating Portion of the Proposed2012-Based IPF Market Basket

ii. Price Proxies for the Capital Portion of the Proposed 2012-Based IPF Market Basket

iii. Summary of all Price Proxies of the Proposed 2012-Based IPF Market Basket

4. Proposed FY 2016 Market Basket Update

5. Proposed Productivity Adjustment
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6. Proposed Labor-related Share

B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1, 2016

1. Determining the Standardized Budget-Neutral Federal Per Diem Base Rate

2. Proposed Update of the Federal Per Diem Base Rate and Electroconvulsive 

Therapy Rate

C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors

2. IPF-PPS Patient-Level Adjustments

a. MS-DRG Assignment

b. Payment for Comorbid Conditions 

3. Patient Age Adjustments

4. Variable Per Diem Adjustments

D. Proposed Updates to the IPF PPS Facility-Level Adjustments

1. Proposed Wage Index Adjustment

a. Background

b. Proposed Wage Index for FY 2016

c. OMB Bulletins and Proposed Transitional Wage Index

d. Adjustment for Rural Location and Proposal to Phase Out the Rural Adjustment for IPFs 

Losing Their Rural Adjustment Due to CBSA Changes

e. Budget neutrality adjustment

2. Teaching Adjustment

3. Cost of Living Adjustment for IPFs Located in Alaska and Hawaii

4. Adjustment for IPFs with a Qualifying Emergency Department (ED)
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E. Other Payment Adjustments and Policies

1. Outlier Payment Overview

2. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount

3. Proposed Update to IPF Cost-to-Charge Ratio Ceilings

IV. Updates on Other Payment Policy Issues

A. Implementation of ICD-10-CM and ICD-10-PCS

B. Update on IPF PPS Refinements

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

1. Statutory Authority

2. Covered Entities

3. Considerations in Selecting Quality Measures

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

C. Proposed Removal of Quality Measure from the IPFQR Program Measure Set

D. New Quality Measures Proposed for the FY 2018 Payment Determination and Subsequent 

Years

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the subset measure 

TOB-3a Tobacco Use Treatment at Discharge

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief 

Intervention 

3. Transition Record with Specified Elements Received by Discharged Patients (Discharges 

from an Inpatient Facility to Home/Self Care or Any Other Site of Care) 

4. Timely Transmission of Transition Record (Discharges from an Inpatient Facility to 
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Home/Self Care or Any Other Site of Care)

5. Screening for Metabolic Disorders 

6. Summary of Measures Proposed for Adoption and Removal for FY 2018 and Subsequent 

Years

E. Possible IPFQR Program Measures and Topics for Future Consideration

F. Changes to Reporting Requirements

1. Proposed Changes to Reporting by Age and Quarter 

2. Proposed Changes to Aggregate Population Count Reporting

3. Proposed Changes to Sampling Requirements for FY 2018 Payment Determination and 

Subsequent Years

G. Public Display and Review Requirements

H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements 

2. Proposed Change to the Reporting Periods and Submission Timeframes 

3. Population, Sampling, and Minimum Case Threshold 

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

I. Reconsideration and Appeals Procedures 

J. Exceptions to Quality Reporting Requirements 

VI. Collection of Information Requirements 

A. Wage Estimates

B. ICRs Regarding the Inpatient Psychiatric Quality Reporting (IPFQR) Program

1. Changes in Time Required to Chart-Abstract Data Based on Proposed Reporting 

Requirements
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2. Estimated Burden of IPFQR Program Proposals

C. Summary of Annual Burden Estimates for Proposed Requirements

D. ICRs Regarding the Hospital and Health Care Complex Cost Report 

E. Submission of PRA-Related Comments

VII. Regulatory Impact Analysis

A. Statement of Need

B. Overall Impact

C. Anticipated Effects

1. Budgetary Impact

2. Impact on Providers

3. Results

4. Effects of Updates to the IPFQR Program

5. Effect on Beneficiaries

D. Alternatives Considered

E. Accounting Statement

Regulations Text

Addendum – FY 2016 Proposed Rates and Adjustment Factors 

Acronyms

Because of the many terms to which we refer by acronym in this proposed rule, we are 

listing the acronyms used and their corresponding meanings in alphabetical order below:

ADC Average Daily Census

AHA American Hospital Association

AHE Average Hourly Earning
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BBRA Medicare, Medicaid and SCHIP [State Children's Health Insurance Program] 

Balanced Budget Refinement Act of 1999 (Pub. L. 106-113)

BEA Bureau of Economic Analysis

BLS Bureau of Labor Statistics

CAH Critical Access Hospital

CBSA Core-Based Statistical Area

CCR Cost-to-Charge Ratio

CPI Consumer Price Index

CPI-U Consumer Price Index for all Urban Consumers

DRGs Diagnosis-Related Groups

ECI Employment Cost Index

ESRD End State Renal Disease

FR Federal Register

FTE Full-time equivalent

FY Federal Fiscal Year (October 1 through September 30)

GDP Gross Domestic Product

GME Graduate Medical Education

HHA Home Health Agency

HBIPS Hospital Based Inpatient Psychiatric Services

ICD-9-CM International Classification of Diseases, 9th Revision, Clinical Modification

ICD-10-CM International Classification of Diseases, 10th Revision, Clinical Modification

ICD-10-PCS International Classification of Diseases, 10th Revision, Procedure Coding System

IGI IHS Global Insight, Inc.
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I-O Input - Output

IPFs Inpatient Psychiatric Facilities

IPFQR Inpatient Psychiatric Facilities Quality Reporting 

IRFs Inpatient Rehabilitation Facilities

LOS Length of Stay

LTCHs Long-Term Care Hospitals

MAC Medicare Administrative Contractor

MedPAR Medicare Provider Analysis and Review File

MFP Multifactor Productivity

MMA Medicare Prescription Drug, Improvement, and Modernization Act of 2003

MSA Metropolitan Statistical Area

NAICS North American Industry Classification System

NQF National Quality Forum

OES Occupational Employment Statistics

OMB Office of Management and Budget

OPPS Outpatient Prospective Payment System

PLI Professional Liability Insurance

PPI Producer Price Index

PPS Prospective Payment System

RPL Rehabilitation, Psychiatric, and Long-Term Care 

RY Rate Year (July 1 through June 30)

SCHIP State Children's Health Insurance Program

SNF Skilled Nursing Facility
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SOC Standard Occupational Classification

TEFRA Tax Equity and Fiscal Responsibility Act of 1982 (Pub. L. 97-248)

I. Executive Summary

A. Purpose 

This proposed rule would update the prospective payment rates for Medicare

inpatient hospital services provided by inpatient psychiatric facilities (IPFs) for discharges 

occurring during the fiscal year (FY) beginning October 1, 2015 through September 30, 2016. 

For the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program, it also would change 

the measures collected under the program and modify reporting requirements for all program 

measures.

B. Summary of the Major Provisions

In this proposed rule, we would update the IPF Prospective Payment System (PPS), as 

specified in 42 CFR 412.428. The updates include the following:

 Effective for FY 2016 IPF PPS update, we are proposing to adopt a FY 2012-based IPFspecific market basket. We propose to adjust the FY 2012-based IPF market basket update 

(currently estimated to be 2.7 percent) by a reduction for economy-wide productivity (currently 

estimated to be 0.6 percentage point) as required by section 1886(s)(2)(A)(i) of the Social 

Security Act (the Act), and further reduced by 0.2 percentage point as required by section 

1886(s)(2)(A)(ii) of the Act, resulting in an estimated market basket update of 1.9 percent.

 We propose to update the IPF per diem rate from $728.31 to $745.19. Providers that 

failed to report quality data for FY 2016 payment would receive a proposed FY 2016 per diem 

rate of $730.56. 

 We propose to update the electroconvulsive therapy (ECT) payment from $313.55 to 
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$320.82. Providers that failed to report quality data for FY 2016 payment would receive a 

proposed FY 2016 ECT rate of $314.52.

 We propose to adopt new Office of Management and Budget (OMB) Core-Based 

Statistical Area (CBSA) delineations for the FY 2016 IPF PPS wage index and future IPF PPS 

wage indices. We propose to implement these CBSA changes using a 1-year transition with a 

blended wage index for all providers, consisting of a blend of fifty percent of the FY 2016 IPF 

wage index using the current OMB delineations and fifty percent of the FY 2016 IPF wage index 

using the revised OMB delineations. 

 We propose to phase out the rural adjustment for the 37 rural IPFs that would be 

re-designated as urban IPFs due to the OMB CBSA changes. Specifically, we propose to phase

out the 17 percent rural adjustment for these 37 providers over 3 years (2-thirds of the adjustment 

given in FY 2016, one-third of the adjustment given in FY 2017, and no rural adjustment 

thereafter).

 We propose to use the updated Labor Related Share of 74.9 percent and CBSA rural and

urban wage indices for FY 2016, and establish a wage index budget-neutrality adjustment of 

1.0041.

 We propose to update the fixed dollar loss threshold amount from $8,755 to $9,825 in 

order to maintain outlier payments that are 2 percent of total IPF PPS payments. 

 We propose that the national urban and rural cost-to-charge ratio (CCR) ceilings for FY 

2016 would be 1.6881 and 1.9041, respectively, and the national median CCR would be 0.4675

for urban IPFs and 0.6210 for rural IPFs. The national median CCR is applied to new IPFs that 

have not yet submitted their first Medicare cost report, to IPFs for which the CCR calculation 

data are inaccurate or incomplete, or to IPFs whose overall CCR exceeds 3 standard deviations 
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above the national geometric mean. These amounts are used in the outlier calculation to 

determine if an IPF’s CCR is statistically accurate and for new providers without an established 

CCR. 

 We note that IPF PPS patient-level and facility-level adjustments, other than those 

mentioned above, would remain the same as in FY 2015. 

In addition: 

 We remind providers that International Classification of Diseases, 10th Revision, Clinical 

Modification/Procedure Coding System (ICD-10-CM/PCS) will be implemented on

October 1, 2015.

 As we continue our analysis for future IPF PPS refinements, we find, from preliminary 

analysis of 2012 to 2013 data, that over 20 percent of IPF stays reported no ancillary costs, such 

as laboratory and drug costs, in their cost reports, or laboratory or drug charges on their claims. 

Because we expect that most patients requiring hospitalization for active psychiatric treatment 

would need drugs and laboratory services, we remind providers that the IPF per diem payment 

rate includes the cost of all ancillary services, including drugs and laboratory services. CMS 

pays only the inpatient psychiatric facility for services furnished to a Medicare beneficiary who 

is an inpatient of that inpatient psychiatric facility, except for certain professional services, and 

payments are considered to be payments in full for all inpatient hospital services provided 

directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

For the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program, we are making 

several proposals related to measures and several proposals related to data submission for the 

IPFQR Program measures. We are proposing to adopt five new measures beginning with the 

fiscal year (FY) 2018 payment determination:
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 TOB-3 - Tobacco Use Treatment Provided or Offered at Discharge and the subset 

measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);

 SUB-2 - Alcohol Use Brief Intervention Provided or Offered and the subset measure 

SUB-2a (NQF #1663);

 Transition Record with Specified Elements Received by Discharged Patients (Discharges 

from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF) #0647);

 Timely Transmission of Transition Record (Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care) (NQF #0648); and

 Screening for Metabolic Disorders.

If Transition Record with Specified Elements Received by Discharged Patients (Discharges from 

an Inpatient Facility to Home/Self Care or Any Other Site of Care) is adopted, we are proposing 

to remove Hospital Based Inpatient Psychiatric Services (HBIPS)-6 Post-Discharge Continuing 

Care Plan (NQF #0557). Likewise, if Timely Transmission of Transition Record (Discharges 

from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648) is 

adopted, we are proposing to remove HBIPS-7 Post-Discharge Continuing Care Plan 

Transmitted to the Next Level of Care Provider Upon Discharge (NQF #0558). We are also 

proposing to remove one measure, HBIPS-4 Patients Discharged on Multiple Antipsychotic 

Medications, beginning with the FY 2017 payment determination.

We are also making several proposals regarding how facilities should report data for 

IPFQR Program measures: 

 We are proposing to require that measures be reported as a single yearly count rather than 

by quarter and age beginning with the FY 2017 payment determination;
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 We are proposing to require that aggregate population counts be reported as a single

yearly number rather than by quarter beginning with the FY 2017 payment determination; and

 We are proposing to allow uniform sampling for certain measures beginning with the 

FY 2018 payment determination.

C. Summary of Impacts

Provision Description Total Transfers 

FY 2016 IPF PPS 

payment rate update

The overall economic impact of this 

proposed rule is an estimated $80 

million in increased payments to IPFs 

during FY 2016.

Provision Description Costs

New quality reporting 

program requirements 

The total costs beginning in FY 2016

for IPFs as a result of the proposed 

new quality reporting requirements are 

estimated to be $6.31 million.

II. Background

A. Overview of the Legislative Requirements for the IPF PPS

Section 124 of the Medicare, Medicaid, and SCHIP (State Children's Health Insurance 

Program) Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113) required the 

establishment and implementation of an IPF PPS. Specifically, section 124 of the BBRA

mandated that the Secretary of the Department Health and Human Services (the Secretary)

develop a per diem PPS for inpatient hospital services furnished in psychiatric hospitals and 

psychiatric units including an adequate patient classification system that reflects the differences 

in patient resource use and costs among psychiatric hospitals and psychiatric units. 

Section 405(g)(2) of the Medicare Prescription Drug, Improvement, and Modernization 

Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF PPS to distinct part psychiatric units of 

critical access hospitals (CAHs). 
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Section 3401(f) of the Patient Protection and Affordable Care Act (Pub. L. 111-148) as 

amended by section 10319(e) of that Act and by section 1105(d) of the Health Care and 

Education Reconciliation Act of 2010 (Pub. L. 111-152) (hereafter referred to as “the Affordable 

Care Act”) added subsection (s) to section 1886 of the Act.

Section 1886(s)(1) of the Act titled “Reference to Establishment and Implementation of 

System” refers to section 124 of the BBRA, which relates to the establishment of the IPF PPS. 

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity 

adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the Rate Year

(RY) beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. For 

the RY beginning in 2015 (that is, FY 2016), the current estimate of the productivity adjustment 

would be equal to 0.6 percentage point, which we are proposing in this FY 2016 proposed rule. 

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that 

reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the 

Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 

2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2

percentage point. We are proposing that reduction in this FY 2016 IPF PPS proposed rule.

Section 1886(s)(4) of the Act requires the establishment of a quality data reporting 

program for the IPF PPS beginning in RY 2014. 

To implement and periodically update these provisions, we have published various 

proposed and final rules in the Federal Register. For more information regarding these rules, 

see the CMS website at http://www.cms.hhs.gov/InpatientPsychFacilPPS/ .

B. Overview of the IPF PPS

The November 2004 IPF PPS final rule (69 FR 66922) established the IPF PPS, as 
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required by section 124 of the BBRA and codified at subpart N of part 412 of the Medicare 

regulations. The November 2004 IPF PPS final rule set forth the per diem Federal rates for the 

implementation year (the 18-month period from January 1, 2005 through June 30, 2006), and 

provided payment for the inpatient operating and capital costs to IPFs for covered psychiatric 

services they furnish (that is, routine, ancillary, and capital costs, but not costs of approved 

educational activities, bad debts, and other services or items that are outside the scope of the IPF 

PPS). Covered psychiatric services include services for which benefits are provided under the 

fee-for-service Part A (Hospital Insurance Program) of the Medicare program. 

The IPF PPS established the Federal per diem base rate for each patient day in an IPF 

derived from the national average daily routine operating, ancillary, and capital costs in IPFs in 

FY 2002. The average per diem cost was updated to the midpoint of the first year under the IPF 

PPS, standardized to account for the overall positive effects of the IPF PPS payment adjustments, 

and adjusted for budget-neutrality. 

The Federal per diem payment under the IPF PPS is comprised of the Federal per diem 

base rate described above and certain patient- and facility-level payment adjustments that were 

found in the regression analysis to be associated with statistically significant per diem cost 

differences.

The patient-level adjustments include age, Diagnosis-Related Group (DRG) assignment, 

comorbidities, and variable per diem adjustments to reflect higher per diem costs in the early 

days of an IPF stay. Facility-level adjustments include adjustments for the IPF's wage index, 

rural location, teaching status, a cost-of-living adjustment for IPFs located in Alaska and Hawaii, 

and the presence of a qualifying emergency department (ED). 

The IPF PPS provides additional payment policies for: outlier cases; interrupted stays; 
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and a per treatment adjustment for patients who undergo electroconvulsive therapy (ECT). 

During the IPF PPS mandatory 3-year transition period, stop-loss payments were also provided;

however, since the transition ended in 2008, these payments are no longer available.

A complete discussion of the regression analysis that established the IPF PPS adjustment 

factors appears in the November 2004 IPF PPS final rule (69 FR 66933 through 66936). 

Section 124 of the BBRA did not specify an annual rate update strategy for the IPF PPS 

and was broadly written to give the Secretary discretion in establishing an update methodology. 

Therefore, in the November 2004 IPF PPS final rule, we implemented the IPF PPS using the 

following update strategy:

 Calculate the final Federal per diem base rate to be budget-neutral for the 18-month 

period of January 1, 2005 through June 30, 2006.

 Use a July 1 through June 30 annual update cycle.

 Allow the IPF PPS first update to be effective for discharges on or after July 1, 2006 

through June 30, 2007.

In RY 2012, we proposed and finalized switching the IPF PPS payment rate update from 

a rate year that begins on July 1 and ends on June 30 to one that coincides with the Federal fiscal 

year that begins October 1 and ends on September 30. In order to transition from one timeframe 

to another, the RY 2012 IPF PPS covered a 15-month period from July 1, 2011 through 

September 30, 2012. Therefore, the update cycle for FY 2016 will be October 1, 2015 through 

September 30, 2016. For further discussion of the 15-month market basket update for RY 2012 

and changing the payment rate update period to coincide with a FY period, we refer readers to 

the RY 2012 IPF PPS proposed rule (76 FR 4998) and the RY 2012 IPF PPS final rule (76 FR 

26432).
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C. Annual Requirements for Updating the IPF PPS

In November 2004, we implemented the IPF PPS in a final rule that appeared in the 

November 15, 2004 Federal Register (69 FR 66922). In developing the IPF PPS, to ensure that 

the IPF PPS is able to account adequately for each IPF's case-mix, we performed an extensive 

regression analysis of the relationship between the per diem costs and certain patient and facility 

characteristics to determine those characteristics associated with statistically significant cost 

differences on a per diem basis. For characteristics with statistically significant cost differences, 

we used the regression coefficients of those variables to determine the size of the corresponding 

payment adjustments. 

In that final rule, we explained that we believe it is important to delay updating the 

adjustment factors derived from the regression analysis until we have IPF PPS data that include 

as much information as possible regarding the patient-level characteristics of the population that 

each IPF serves. Therefore, we indicated that we did not intend to update the regression analysis 

and the patient- and facility-level adjustments until we complete that analysis. Until that analysis 

is complete, we stated our intention to publish a notice in the Federal Register each spring to 

update the IPF PPS (71 FR 27041). We have begun the necessary analysis to make refinements 

to the IPF PPS using more current data to set the adjustment factors; however, we are not 

proposing any refinements in this proposed rule. Rather, as explained in section IV.B. of this 

proposed rule, we expect that in future rulemaking we will be ready to propose potential 

refinements.

In the May 6, 2011 IPF PPS final rule (76 FR 26432), we changed the payment rate 

update period to a RY that coincides with a FY update. Therefore, update notices are now 

published in the Federal Register in the summer to be effective on October 1. When proposing 
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changes in IPF payment policy, a proposed rule would be issued in the spring and the final rule 

in the summer in order to be effective on October 1. For further discussion on changing the IPF 

PPS payment rate update period to a RY that coincides with a FY, see the IPF PPS final rule 

published in the Federal Register on May 6, 2011 (76 FR 26434 through 26435). For a detailed 

list of updates to the IPF PPS, see 42 CFR 412.428. 

Our most recent IPF PPS annual update occurred in an August 6, 2014, Federal Register 

final rule (79 FR 45938) (hereinafter referred to as the August 2014 IPF PPS final rule) that set 

forth updates to the IPF PPS payment rates for FY 2015. That rule updated the IPF PPS per 

diem payment rates that were published in the August 2013 IPF PPS notice (78 FR 46734) in 

accordance with our established policies.

III. Provisions of the Proposed Rule

A. Proposed Market Basket for the IPF PPS

1. Background

The input price index that was used to develop the IPF PPS was the Excluded Hospital 

with Capital market basket. This market basket was based on 1997 Medicare cost reports for 

Medicare participating IRFs, IPFs, LTCHs, cancer hospitals, and children’s hospitals. Although 

‘‘market basket’’ technically describes the mix of goods and services used in providing health

care at a given point in time, this term is also commonly used to denote the input price index 

(that is, cost category weights and price proxies) derived from that market basket. Accordingly, 

the term ‘‘market basket,’’ as used in this document, refers to an input price index.

Beginning with the May 2006 IPF PPS final rule (71 FR 27046 through 27054), IPF PPS 

payments were updated using a 2002-based RPL market basket reflecting the operating and 

capital cost structures for freestanding IRFs, freestanding IPFs, and LTCHs. Cancer and 
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children’s hospitals were excluded from the RPL market basket because their payments are 

based entirely on reasonable costs subject to rate-of-increase limits established under the 

authority of section 1886(b) of the Act and not through a PPS. Also, the 2002 cost structures for 

cancer and children’s hospitals are noticeably different than the cost structures of freestanding 

IRFs, freestanding IPFs, and LTCHs. See the May 2006 IPF PPS final rule (71 FR 27046 

through 27054) for a complete discussion of the 2002-based RPL market basket.

In the May 1, 2009 IPF PPS notice (74 FR 20376), we expressed our interest in exploring 

the possibility of creating a stand-alone IPF market basket that reflects the cost structures of only 

IPF providers. One available option was to combine the Medicare cost report data from 

freestanding IPF providers with Medicare cost report data from hospital-based IPF providers. 

We indicated that an examination of the Medicare cost report data comparing freestanding IPFs 

and hospital-based IPFs showed differences between cost levels and cost structures. At that 

time, we were unable to fully understand these differences even after reviewing explanatory 

variables such as geographic variation, case mix (including DRG, comorbidity, and age), urban 

or rural status, teaching status, and presence of a qualifying emergency department. As a result, 

we continued to research ways to reconcile the differences and solicited public comment for 

additional information that might help us to better understand the reasons for the variations in 

costs and cost structures, as indicated by the Medicare cost report data (74 FR 20376). We 

summarized the public comments we received and our responses in the April 2010 IPF PPS 

notice (75 FR 23111 through 23113). Despite receiving comments from the public on this issue, 

we were still unable to sufficiently reconcile the observed differences in costs and cost structures 

between hospital-based and freestanding IPFs, and, therefore, we did not believe it to be 
CMS-1627-P 23

appropriate at that time to incorporate data from hospital-based IPFs with those of freestanding 

IPFs to create a stand-alone IPF market basket.

Beginning with the RY 2012 IPF PPS final rule (76 FR 26432), IPF PPS payments were 

updated using a 2008-based RPL market basket reflecting the operating and capital cost 

structures for freestanding IRFs, freestanding IPFs, and LTCHs. The major changes for RY 

2012 included: updating the base year from FY 2002 to FY 2008; using a more specific 

composite chemical price proxy; breaking the professional fees cost category into 2 separate 

categories (Labor-related and Nonlabor-related); and adding 2 additional cost categories 

(Administrative and Facilities Support Services and Financial Services), which were previously 

included in the residual All Other Services cost categories. The RY 2012 IPF PPS proposed rule 

(76 FR 4998) and RY 2012 final rule (76 FR 26432) contain a complete discussion of the 

development of the 2008-based RPL market basket.

For FY 2016, we are proposing to create a 2012-based IPF market basket, using Medicare 

cost report data for both freestanding and hospital-based IPFs. In the following discussion, we 

provide an overview of the proposed market basket and describe the methodologies used to 

determine the operating and capital portions of the proposed 2012-based IPF market basket.

2. Overview of the Proposed 2012-Based IPF Market Basket

The proposed 2012-based IPF market basket is a fixed-weight, Laspeyres-type price 

index. A Laspeyres price index measures the change in price, over time, of the same mix of 

goods and services purchased in the base period. Any changes in the quantity or mix of goods 

and services (that is, intensity) purchased over time relative to a base period are not measured.

The index itself is constructed in 3 steps. First, a base period is selected (in this proposed 

rule, the base period is FY 2012) and total base period expenditures are estimated for a set of 
CMS-1627-P 24

mutually exclusive and exhaustive spending categories with the proportion of total costs that 

each category represents being calculated. These proportions are called cost or expenditure 

weights. Second, each expenditure category is matched to an appropriate price or wage variable, 

referred to as a price proxy. In nearly every instance, these price proxies are derived from 

publicly available statistical series that are published on a consistent schedule (preferably at least 

on a quarterly basis). Finally, the expenditure weight for each cost category is multiplied by the 

level of its respective price proxy. The sum of these products (that is, the expenditure weights 

multiplied by their price levels) for all cost categories yields the composite index level of the 

market basket in a given period. Repeating this step for other periods produces a series of 

market basket levels over time. Dividing an index level for a given period by an index level for 

an earlier period produces a rate of growth in the input price index over that timeframe.

As noted above, the market basket is described as a fixed-weight index because it 

represents the change in price over time of a constant mix (quantity and intensity) of goods and 

services needed to furnish IPF services. The effects on total expenditures resulting from changes 

in the mix of goods and services purchased subsequent to the base period are not measured. For 

example, an IPF hiring more nurses to accommodate the needs of patients would increase the 

volume of goods and services purchased by the IPF, but would not be factored into the price 

change measured by a fixed-weight IPF market basket. Only when the index is rebased would 

changes in the quantity and intensity be captured, with those changes being reflected in the cost 

weights. Therefore, we rebase the market basket periodically so that the cost weights reflect 

recent changes in the mix of goods and services that IPFs purchase (facility inputs) to furnish 

inpatient care between base periods. 

3. Creating an IPF-specific Market Basket
CMS-1627-P 25

As discussed in section III.A.1, over the last several years we have been exploring the 

possibility of creating a stand-alone, or IPF-specific, market basket that reflects the cost 

structures of only IPF providers. The major cost weights for the 2008-based RPL market basket 

were calculated using Medicare cost report data for freestanding facilities only. We used 

freestanding facilities due to concerns regarding our ability to incorporate Medicare cost report 

data for hospital-based providers. In the FY 2015 IPF PPS final rule (79 FR 45941), we 

presented several of these concerns (as stated below) but explained that we would continue to 

research the possibility of creating an IPF-specific market basket to update IPF PPS payments. 

Since the FY 2015 IPF PPS final rule, we have performed additional research on the 

Medicare cost report data available for hospital-based IPFs and evaluated these concerns. We 

subsequently concluded from this research that Medicare cost report data for both hospitalbased IPFs and freestanding IPFs can be used to calculate the major market basket cost weights 

for a stand-alone IPF market basket. We have developed a detailed methodology to derive 

market basket cost weights that are representative of the universe of IPF providers. We believe 

the use of this proposed IPF market basket is a technical improvement over the RPL market 

basket that is currently used to update IPF PPS payments. As a result, in this FY 2016 IPF PPS 

proposed rule, we are proposing a 2012-based IPF market basket that reflects data for both 

freestanding and hospital-based IPFs. Below we discuss our prior concerns and provide reasons 

for why we now feel it is appropriate to create a stand-alone IPF market basket using Medicare 

cost report data for both hospital-based and freestanding IPFs.

One concern we discussed in the FY 2015 IPF PPS final rule (79 FR 45941) about using 

the hospital-based IPF Medicare cost report data was the cost level differences for hospitalbased IPFs relative to freestanding IPFs were not readily explained by the specific 
CMS-1627-P 26

characteristics of the individual providers and the patients that they serve (for example, 

characteristics related to case mix, urban/rural status, teaching status, or presence of a qualified 

emergency department). To address this concern, we used regression analysis to evaluate the 

effect of including hospital-based IPF Medicare cost report data in the calculation of cost 

distributions. A more detailed description of these regression models can be found in the FY 

2015 IPF final rule (79 FR 45941). Based on this analysis, we concluded that the inclusion of 

those IPF providers with unexplained variability in costs did not significantly impact the cost 

weights and, therefore, should not be a major cause of concern.

Another concern regarding the incorporation of hospital-based IPF data into the 

calculation of the market basket cost weights was the complexity of the Medicare cost report 

data for these providers. The freestanding IPFs independently submit a Medicare cost report for 

their facilities, making it relatively straightforward to obtain the cost categories necessary to 

determine the major market basket cost weights. However, Medicare cost report data submitted 

for a hospital-based IPF are embedded in the Medicare cost report submitted for the entire 

hospital facility in which the IPF is located. In order to use Medicare cost report data from 

these providers, we needed to determine the appropriate adjustments to apply to the data to 

ensure that the cost weights we obtained would represent only the hospital-based IPF (not the 

hospital as a whole). Over the past year, we worked to develop detailed methodologies to 

calculate the major cost weights for both freestanding and hospital-based IPFs. We believe that 

our proposed methodologies and the resulting cost weights, described in section III.A.3.a.i 

below, are reasonable and appropriate. We welcome public comments on these proposals. 

We also evaluated the differences in cost weights for hospital-based and freestanding 

IPFs and found the most significant differences occurred for salaries and pharmaceutical costs. 
CMS-1627-P 27

Specifically, the hospital-based IPF salary cost weights tend to be lower than those of 

freestanding IPFs while hospital-based IPF pharmaceutical cost weights tend to be higher than 

those of freestanding IPFs. Our proposed methodology for deriving costs for each of these 

categories can be found in section III.A.3.a.i below. We will continue to research and monitor 

these cost shares to ensure that the differences are explainable.

In summary, our research over the past year allowed us to evaluate the appropriateness 

of including hospital-based IPF data in the calculation of the major cost weights for an IPF 

market basket. We believe that the proposed methodologies for deriving the cost weights give 

us the ability to create a stand-alone IPF market basket that reflects the cost structure of the 

universe of IPF providers. Therefore, we believe that the use of this proposed 2012-based IPF 

market basket to update IPF PPS payments is an improvement over the current 2008-based RPL 

market basket.

a. Development of Cost Categories and Weights

i. Medicare Cost Reports 

The proposed 2012-based IPF market basket consists of seven major cost categories 

derived from the FY 2012 Medicare cost reports (CMS Form 2552-10) for freestanding and 

hospital-based IPFs, including Wages and Salaries, Employee Benefits, Contract Labor, 

Pharmaceuticals, Professional Liability Insurance (PLI), Capital, and a residual. The residual 

reflects all remaining costs that are not captured in the other six cost categories. The FY 2012 

cost reports include providers whose cost report begin date is on or between 

October 1, 2011, and September 30, 2012. We choose to use FY 2012 as the base year because 

we believe that the Medicare cost reports for this year represent the most recent, complete set of 

Medicare cost report data available for IPFs at the time of rulemaking.
CMS-1627-P 28

Prior Medicare cost report data used to develop the RPL market basket showed large 

differences between some providers’ Medicare length of stay (LOS) and total facility LOS. 

Since our goal is to measure cost weights that are reflective of case mix and practice patterns 

associated with providing services to Medicare beneficiaries, we limited our selection of 

Medicare cost reports used in the RPL market basket to those facilities that had a Medicare LOS 

that was within a comparable range of their total facility average LOS. For the 2008-based RPL 

market basket, we used those IPF Medicare cost reports whose average Medicare LOS was 

within 30 percent of the average facility LOS if the facility LOS was greater than or equal to 15 

days. For those IPFs whose average facility LOS was less than 15 days, the Medicare LOS had 

to be within 50 percent of the average facility LOS. When applying the LOS trim to derive the 

2008-based RPL market basket, we found that those providers that were excluded (of which 

seventy percent were IPFs) had an average facility LOS (40 days) that was 2 times larger than 

the Medicare LOS (20 days). 

To create the proposed 2012-based IPF market basket, we reevaluated the LOS trim 

based on FY 2012 Medicare cost report data and the inclusion of hospital-based providers. 

Based on our analysis of the data, we are proposing to apply a less restrictive LOS trim to derive 

the 2012-based IPF market basket than was applied to derive the RPL market basket. For 

freestanding IPFs, we propose to define the Medicare and facility LOS as those reported on line 

14 of Worksheet S-3, Part I (consistent with the RPL market basket method). For hospital-based 

IPFs, we are proposing to use line 16 of Worksheet S-3, Part I to determine the Medicare and 

facility LOS. To derive the proposed 2012-based IPF market basket, for those IPFs with an 

average facility LOS of greater than or equal to 15 days, we are proposing to include IPFs where 

the Medicare LOS is within 50 percent (higher or lower) of the average facility LOS. For those 
CMS-1627-P 29

IPFs whose average facility LOS is less than 15 days, we are proposing to include IPFs where 

the Medicare LOS is within 95 percent (higher or lower) of the facility LOS.

This less restrictive trim increases the number of IPFs included in the derivation of the 

market basket, particularly for those providers where the Medicare LOS and facility LOS is 

within 5 days. Applying the proposed trim results in IPF Medicare cost reports with an average 

Medicare LOS of 12 days, average facility LOS of 10 days, and Medicare utilization (as 

measured by Medicare inpatient IPF days as a percentage of total facility days) of 30 percent. If 

we were to apply the same trim as was applied for the 2008-based RPL market basket, it would 

result in IPF Medicare cost reports with an average Medicare LOS of 12 days, average facility 

LOS of 9 days, and Medicare utilization of 31 percent. Those providers that were excluded from 

the proposed 2012-based IPF market basket have an average Medicare LOS of 22 days, average 

facility LOS of 49 days, and a Medicare utilization of 5 percent. Of those Medicare cost reports 

excluded from the proposed 2012-based IPF market basket, about 70 percent of these were 

freestanding providers whereas freestanding providers represent about 30 percent of all IPFs. 

We believe the proposed trim is a technical improvement as data from more IPFs is used while 

still being reflective of case mix and practice patterns associated with providing services to 

Medicare beneficiaries. 

We applied this LOS trim to first obtain a set of cost reports for facilities that have a 

Medicare LOS within a comparable range of their total facility LOS. Using the resulting set of 

FY 2012 Medicare cost reports for freestanding IPFs and hospital-based IPFs, we are proposing 

to calculate costs for the six major cost categories (Wages and Salaries, Employee Benefits, 

Contract Labor, Professional Liability Insurance, Pharmaceuticals, and Capital). 

Similar to the 2008-based RPL market basket major cost weights, the proposed 2012-
CMS-1627-P 30

based IPF market basket cost weights reflect Medicare allowable costs (routine, ancillary and 

capital costs) that are eligible for inclusion under the IPF PPS payments. We define Medicare 

allowable costs for freestanding facilities as cost centers (CMS Form 2552-10): 30 through 35, 

50 through 76 (excluding 52 and 75), 90 through 91, and 93. We define Medicare allowable 

costs for hospital-based facilities as cost centers (CMS Form 2552-10): 40, 50 through 76 

(excluding 52 and 75), 90 through 91, and 93. For freestanding IPFs, total Medicare allowable 

costs are equal to the total costs as reported on Worksheet B, part I, column 26. For hospitalbased IPFs, total Medicare allowable costs are equal to total costs for the IPF inpatient unit after 

the allocation of overhead costs (Worksheet B, part I, column 26, line 40) and a portion of total 

ancillary costs. We calculate the portion of ancillary costs attributable to the hospital-based IPF 

for a given ancillary cost center by multiplying total facility ancillary costs for the specific cost 

center (as reported on Worksheet B, Part I, column 26) by the ratio of IPF Medicare ancillary 

costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total 

Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all 

relevant PPS (that is, IPPS, IRF, IPF and Skilled Nursing Facility (SNF))). 

Below we provide a description of the proposed methodologies used to derive costs for 

the six major cost categories.

Wages and Salaries Costs

For freestanding IPFs, Wages and Salaries costs are derived as the sum of routine 

inpatient salaries, ancillary salaries, and a proportion of overhead (or general service cost center) 

salaries as reported on Worksheet A, column 1. Since overhead salary costs are attributable to 

the entire IPF, we only include the proportion attributable to the Medicare allowable cost centers. 

We estimate the proportion of overhead salaries that are attributed to Medicare allowable costs 
CMS-1627-P 31

centers by multiplying the ratio of Medicare allowable salaries to total salaries (Worksheet A, 

column 1, line 200) times total overhead salaries. A similar methodology was used to derive 

Wages and Salaries costs in the 2008-based RPL market basket.

For hospital-based IPFs, Wages and Salaries costs are derived as the sum of inpatient unit 

wages and salaries (Worksheet A, column 1, line 40) and a portion of salary costs attributable to 

total facility ancillary and overhead cost centers as these cost centers are shared with the entire 

facility. We calculate the portion of ancillary salaries attributable to the hospital-based IPF for a 

given ancillary cost center by multiplying total facility ancillary salary costs for the specific cost 

center (as reported on Worksheet A, column 1) by the ratio of IPF Medicare ancillary costs for 

the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare 

ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant 

PPS units (that is, IPPS, IRF, IPF and SNF)). For example, if hospital-based IPF Medicare 

laboratory costs represent 10 percent of the total Medicare laboratory costs for the entire facility, 

then 10 percent of total facility laboratory salaries (as reported in Worksheet A, column 1, line 

60) would be attributable to the hospital-based IPF. We believe it is appropriate to use only a 

portion of the ancillary costs in the market basket cost weight calculations since the hospitalbased IPF only utilizes a portion of the facility’s ancillary services. We believe the ratio of 

reported IPF Medicare costs to reported total Medicare costs provides a reasonable estimate of 

the ancillary services utilized, and costs incurred, by the hospital-based IPF. 

We calculate the portion of overhead salary costs attributable to hospital-based IPFs by 

multiplying the total overhead costs attributable to the hospital-based IPF (sum of columns 4

through18 on Worksheet B, part I, line 40) by the ratio of total facility overhead salaries (as 

reported on Worksheet A, column 1, lines 4 through18) to total facility overhead costs (as 
CMS-1627-P 32

reported on Worksheet A, column 7, lines 4 through18). This methodology assumes the 

proportion of total costs related to salaries for the overhead cost centers is similar for all inpatient 

units (that is, acute inpatient or inpatient psychiatric). Since the 2008-based RPL market basket 

did not include hospital-based providers, this proposed methodology cannot be compared to the 

derivation of Wages and Salaries costs in the 2008-based RPL market basket.

Employee Benefits Costs 

Effective with our implementation of CMS Form 2552-10, CMS began collecting 

Employee Benefits and Contract Labor data on Worksheet S-3, Part V. Previously, with CMS 

Form 2540-96, Employee Benefits and Contract Labor data were reported on Worksheet S-3, 

part II, which was applicable to only IPPS providers and, therefore, these data were not available 

for the derivation of the RPL market basket. Due to the lack of such data, the Employee Benefits 

cost weight for the 2008-based RPL market basket was derived by multiplying the 2008-based 

RPL market basket Wages and Salaries cost weight by the ratio of the IPPS hospital market 

basket Employee Benefits cost weight to the IPPS hospital market basket Wages and Salaries 

cost weight. Similarly, the Contract Labor cost weight for the 2008-based RPL market basket 

was derived by multiplying the 2008-based RPL market basket Wages and Salaries cost weight 

by the ratio of the IPPS hospital market basket Contract Labor cost weight to the IPPS hospital 

market basket Wages and Salaries cost weight.

For FY 2012 Medicare cost report data, while there were providers that did report data on 

Worksheet S-3, part V, many providers did not complete this worksheet. However, we believe 

we had a large enough sample to enable us to produce reasonable Employee Benefits cost

weights. We continue to encourage all providers to report these data on the Medicare cost report. 

For freestanding IPFs, Employee Benefits costs are equal to the data reported on 
CMS-1627-P 33

Worksheet S-3, Part V, line 2, column 2. 

For hospital-based IPFs, we calculate total benefits as the sum of benefit costs reported 

on Worksheet S-3 Part V, line 3, column 2, and a portion of ancillary benefits and overhead

benefits for the total facility. Ancillary benefits attributable to the hospital-based IPF are 

calculated by multiplying ancillary salaries for the hospital-based IPF as determined in the 

derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits 

to total facility salaries. Similarly, overhead benefits attributable to the hospital-based IPF are 

calculated by multiplying overhead salaries for the hospital-based IPF as determined in the 

derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits 

to total facility salaries.

Contract Labor Costs

Similar to the RPL and IPPS market baskets, Contract Labor costs are primarily 

associated with direct patient care services. Contract labor costs for other services such as 

accounting, billing, and legal are calculated separately using other government data sources as 

described in section III.A.3.a.ii. As discussed above in the Employee Benefits section, we now 

have data reported on Worksheet S-3, Part V that we can use to derive the Contract Labor cost 

weight for the 2012-based IPF market basket. For freestanding IPFs, Contract Labor costs are 

based on data reported on Worksheet S-3, part V, column 1, line 2 and for hospital-based IPFs

Contract Labor costs are based on line 3 of this same worksheet. As previously noted, for FY 

2012 Medicare cost report data, while there were providers that did report data on Worksheet S3, part V, many providers did not complete this worksheet. However, we believe we had a large 

enough sample to enable us to produce a reasonable Contract Labor cost weight. We continue to 

encourage all providers to report these data on the Medicare cost report. 
CMS-1627-P 34

Pharmaceuticals Costs

For freestanding IPFs, pharmaceuticals costs are based on non-salary costs reported on 

Worksheet A, column 7 less Worksheet A, column 1 for the pharmacy cost center (line 15) and 

drugs charged to patients cost center (line 73). 

For hospital-based IPFs, pharmaceuticals costs are based on a portion of the non-salary 

pharmacy costs and a portion of the non-salary drugs charged to patient costs reported for the 

total facility. Non-salary pharmacy costs attributable to the hospital-based IPF are calculated by 

multiplying total pharmacy costs attributable to the hospital-based IPF (as reported on Worksheet 

B, column 15, line 40) by the ratio of total non-salary pharmacy costs (Worksheet A, column 2, 

line 15) to total pharmacy costs (sum of Worksheet A, column 1 and 2 for line 15) for the total 

facility. Non-salary drugs charged to patient costs attributable to the hospital-based IPF are 

calculated by multiplying total non-salary drugs charged to patient costs (Worksheet B, part I, 

column 0, line 73 plus Worksheet B, part I, column 15, line 73 less Worksheet A, column 1, line 

73) for the total facility by the ratio of Medicare drugs charged to patient ancillary costs for the 

IPF unit (as reported on Worksheet D-3 for IPF subproviders, line 73, column 3) to total 

Medicare drugs charged to patients ancillary costs for the total facility (equal to the sum of 

Worksheet D-3, line 73, column 3, for all relevant PPS (i.e. IPPS, IRF, IPF and SNF)). 

Professional Liability Insurance (PLI) Costs

For freestanding IPFs, PLI costs (often referred to as malpractice costs) are equal to 

premiums, paid losses and self-insurance costs reported on Worksheet S-2, line 118, columns 1 

through 3. 

For hospital-based IPFs, we assume that the PLI weight for the total facility is similar to 

the hospital-based IPF unit since the only data reported on this worksheet is for the entire 
CMS-1627-P 35

facility. Therefore, hospital-based IPF PLI costs are equal to total facility PLI (as reported on 

Worksheet S-2, line 118, columns 1 through 3) divided by total facility costs (as reported on 

Worksheet A, line 200) times hospital-based IPF Medicare allowable total costs. 

Capital Costs

For freestanding IPFs, capital costs are equal to Medicare allowable capital costs as 

reported on Worksheet B, Part II, column 26. 

For hospital-based IPFs, capital costs are equal to IPF inpatient capital costs (as reported 

on Worksheet B, part II, column 26, line 40) and a portion of IPF ancillary capital costs. We 

calculate the portion of ancillary capital costs attributable to the hospital-based IPF for a given 

cost center by multiplying total facility ancillary capital costs for the specific ancillary cost 

center (as reported on Worksheet B, Part II, column 26) by the ratio of IPF Medicare ancillary 

costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total 

Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all 

relevant PPS (that is, IPPS, IRF, IPF and SNF)). 

i. Final Major Cost Category Computation

After we derive costs for the six major cost categories for each provider using the 

Medicare cost report data as described above, we trim the data for outliers based on the 

following steps. First, we divide the costs for each of the six categories by total Medicare 

allowable costs calculated for the provider to obtain cost weights for the universe of IPF 

providers. Next, we apply a mutually exclusive top and bottom 5 percent trim for each cost 

weight to remove outliers. After the outliers have been removed, we sum the costs for each 

category across all remaining providers. We then divide this by the sum of total Medicare 

allowable costs across all remaining providers to obtain a cost weight for the proposed 2012-
CMS-1627-P 36

based IPF market basket for the given category. Finally, we calculate the residual “All Other” 

cost weight that reflects all remaining costs that are not captured in the six cost categories listed 

above. See Table 1 below for the resulting cost weights for these major cost categories that we 

obtain from the Medicare cost reports.

TABLE 1: Major Cost Categories as Derived from Medicare Cost Reports

Major Cost Categories

2012-Based IPF 

(Percent)

2008-Based RPL 

(Percent)

Wages and Salaries 50.8 47.4

Employee Benefits1 13.0 12.3

Contract Labor1 1.4 2.6

Professional Liability 

Insurance (Malpractice)

1.1 0.8

Pharmaceuticals 4.8 6.5

Capital 7.0 8.4

All Other 22.0 22.0

*Total may not sum to 100 due to rounding.

1\ Due to the lack of Medicare cost report data, the Employee Benefits and Contract Labor cost weights 

in the 2008-based RPL market basket were based on the IPPS market basket.

The Wages and Salaries cost weight obtained directly from the Medicare cost reports for 

the proposed 2012-based IPF market basket is approximately 3 percentage points higher than the 

Wages and Salaries cost weight for the 2008-based RPL market basket. This is the result of 

freestanding IPFs having a larger percentage of costs attributable to labor than freestanding 

Inpatient Rehabilitation Facilities (IRF) and Long-term care hospitals. These latter facilities 

were included in the 2008-based RPL market basket. 

As we did for the 2008-based RPL market basket, we propose to allocate the Contract 

Labor cost weight to the Wages and Salaries and Employee Benefits cost weights based on their 

relative proportions under the assumption that contract labor costs are comprised of both wages 

and salaries and employee benefits. The Contract Labor allocation proportion for Wages and 

Salaries is equal to the Wages and Salaries cost weight as a percent of the sum of the Wages and 

Salaries cost weight and the Employee Benefits cost weight. This rounded percentage is 80 

percent; therefore, we propose to allocate 80 percent of the Contract Labor cost weight to the 
CMS-1627-P 37

Wages and Salaries cost weight and 20 percent to the Employee Benefits cost weight. Table 2 

shows the Wages and Salaries and Employee Benefit cost weights after Contract Labor cost 

weight allocation for both the proposed 2012-based IPF market basket and 2008-based RPL 

market basket. 

 Table 2–Wages and Salaries and Employee Benefits Cost Weights After Contract Labor 

 Allocation

Major Cost Categories

2012-Based IPF 2008-Based RPL 

Wages and Salaries 51.9 49.4

Employee Benefits 13.3 12.8

i. Derivation of the Detailed Operating Cost Weights 

To further divide the “All Other” residual cost weight estimated from the FY 2012 

Medicare Cost Report data into more detailed cost categories, we propose to use the 2007 

Benchmark Input-Output (I-O) “Use Tables/Before Redefinitions/Purchaser Value” for North 

American Industry Classification System (NAICS) 622000 Hospitals, published by the Bureau of 

Economic Analysis (BEA). These data are publicly available at the following website:

http://www.bea.gov/industry/io_annual.htm 

The BEA Benchmark I–O data are scheduled for publication every five years with the 

most recent data available for 2007. The 2007 Benchmark I–O data are derived from the 2007 

Economic Census and are the building blocks for BEA’s economic accounts. Thus, they 

represent the most comprehensive and complete set of data on the economic processes or 

mechanisms by which output is produced and distributed.

1 BEA also produces Annual I–O 

estimates; however, while based on a similar methodology, these estimates reflect less 

comprehensive and less detailed data sources and are subject to revision when benchmark data 

 

1 http://www.bea.gov/papers/pdf/IOmanual_092906.pdf
CMS-1627-P 38

becomes available. Instead of using the less detailed Annual I–O data, we inflate the 2007 

Benchmark I–O data forward to 2012 by applying the annual price changes from the respective 

price proxies to the appropriate market basket cost categories that are obtained from the 2007 

Benchmark I-O data. We repeat this practice for each year. We then calculate the cost shares 

that each cost category represents of the inflated 2012 data. These resulting 2012 cost shares are 

applied to the All Other residual cost weight to obtain the detailed cost weights for the proposed 

2012-based IPF market basket. For example, the cost for Food: Direct Purchases represents 6.5 

percent of the sum of the ‘‘All Other’’ 2007 Benchmark I–O Hospital Expenditures inflated to 

2012; therefore, the Food: Direct Purchases cost weight represents 6.5 percent of the 2012-based 

IPF market basket’s “All Other” cost category (22.0 percent), yielding a “final” Food: Direct 

Purchases cost weight of 1.4 percent in the proposed 2012-based IPF market basket (0.065 * 22.0 

percent = 1.4 percent). 

Using this methodology, we derive eighteen detailed IPF market basket cost category 

weights from the proposed 2012-based IPF market basket residual cost weight (22.0 percent). 

These categories are: (1) Electricity, (2) Fuel, Oil, and Gasoline (3) Water & Sewerage (4) Food: 

Direct Purchases, (5) Food: Contract Services, (6) Chemicals, (7) Medical Instruments, (8)

Rubber & Plastics, (9) Paper and Printing Products, (10) Miscellaneous Products, (11)

Professional Fees: Labor-related, (12) Administrative and Facilities Support Services, (13)

Installation, Maintenance, and Repair, (14) All Other Labor-related Services, (15) Professional 

Fees: Nonlabor-related, (16) Financial Services, (17) Telephone Services, and (18) All Other 

Nonlabor-related Services. 

iii. Derivation of the Detailed Capital Cost Weights
CMS-1627-P 39

As described in section III.A.3.a.i of this preamble, we are proposing a Capital-Related 

cost weight of 7.0 percent as obtained from the FY 2012 Medicare cost reports for freestanding 

and hospital-based IPF providers. We are proposing to then separate this total Capital-Related 

cost weight into more detailed cost categories. 

Using FY 2012 Medicare cost reports, we are able to group Capital-Related costs into the 

following categories: Depreciation, Interest, Lease, and Other Capital-Related costs. For each 

of these categories, we are proposing to determine separately for hospital-based IPFs and 

freestanding IPFs what proportion of total capital-related costs the category represent. 

For freestanding IPFs, we are proposing to derive the proportions for Depreciation, 

Interest, Lease, and Other Capital-related costs using the data reported by the IPF on Worksheet 

A-7, which is similar to the methodology used for the 2008-based RPL market basket. 

For hospital-based IPFs, data for these four categories are not reported separately for the 

subprovider; therefore, we are proposing to derive these proportions using data reported on 

Worksheet A-7 for the total facility. We are assuming the cost shares for the overall hospital are 

representative for the hospital-based subprovider IPF unit. For example, if depreciation costs 

make up 60 percent of total capital costs for the entire facility, we believe it is reasonable to 

assume that the hospital-based IPF would also have a 60 percent proportion because it is a 

subprovider unit contained within the total facility. 

In order to combine each detailed capital cost weight for freestanding and hospital-based 

IPFs into a single capital cost weight for the proposed 2012-based IPF market basket, we are 

proposing to weight together the shares for each of the categories (Depreciation, Interest, Lease, 

and Other Capital-related costs) based on the share of total capital costs each provider type 

represents of the total capital costs for all IPFs for 2012. Applying this methodology results in 
CMS-1627-P 40

proportions of total capital-related costs for Depreciation, Interest, Lease and Other Capitalrelated costs that are representative of the universe of IPF providers.

We next are proposing to allocate lease costs across each of the remaining detailed 

capital-related cost categories as was done in the 2008-based RPL market basket. This would 

result in 3 primary capital-related cost categories in the proposed 2012-based IPF market basket: 

Depreciation, Interest, and Other Capital-Related costs. Lease costs are unique in that they are 

not broken out as a separate cost category in the proposed 2012-based IPF market basket, but 

rather we are proposing to proportionally distribute these costs among the cost categories of 

Depreciation, Interest, and Other Capital-Related, reflecting the assumption that the underlying 

cost structure of leases is similar to that of capital-related costs in general. As was done under 

the 2008-based RPL market basket, we are proposing to assume that 10 percent of the lease costs 

as a proportion of total capital-related costs represents overhead and assign those costs to the 

Other Capital-Related cost category accordingly. We propose to distribute the remaining lease 

costs proportionally across the 3 cost categories (Depreciation, Interest, and Other CapitalRelated) based on the proportion that these categories comprise of the sum of the Depreciation, 

Interest, and Other Capital-related cost categories (excluding lease expenses). This is the same 

methodology used for the 2008-based RPL market basket. The allocation of these lease 

expenses are shown in Table 3 below.

Finally, we are proposing to further divide the Depreciation and Interest cost categories. 

We are proposing to separate Depreciation into the following 2 categories: (1) Building and 

Fixed Equipment; and (2) Movable Equipment; and proposing to separate Interest into the 

following 2 categories: (1) Government/Nonprofit; and (2) For-profit. 
CMS-1627-P 41

To disaggregate the Depreciation cost weight, we need to determine the percent of total 

Depreciation costs for IPFs that is attributable to Building and Fixed Equipment, which we 

hereafter refer to as the “fixed percentage.” For the proposed 2012-based IPF market basket, we 

are proposing to use slightly different methods to obtain the fixed percentages for hospital-based 

IPFs compared to freestanding IPFs. 

For freestanding IPFs, we are proposing to use depreciation data from Worksheet A-7 of 

the FY 2012 Medicare cost reports, similar to the methodology used for the 2008-based RPL 

market basket. However, for hospital-based IPFs, we determined that the fixed percentage for 

the entire facility may not be representative of the IPF subprovider unit due to the entire facility 

likely employing more sophisticated movable assets that are not utilized by the hospital-based 

IPF. Therefore, for hospital-based IPFs, we are proposing to calculate a fixed percentage using: 

(1) building and fixture capital costs allocated to the subprovider unit as reported on Worksheet 

B, part I line 40 ; and (2) building and fixture capital costs for the top five ancillary cost centers 

utilized by hospital-based IPFs. We propose to weight these 2 fixed percentages (inpatient and 

ancillary) using the proportion that each capital cost type represents of total capital costs in the 

proposed 2012-based IPF market basket. We are proposing to then weight the fixed percentages 

for hospital-based and freestanding IPFs together using the proportion of total capital costs each 

provider type represents. 

To disaggregate the Interest cost weight, we need to determine the percent of total 

interest costs for IPFs that are attributable to government and nonprofit facilities, which we 

hereafter refer to as the “nonprofit percentage.” For the IPF market basket, we are proposing to 

use interest costs data from Worksheet A-7 of the FY 2012 Medicare cost reports for both 

freestanding and hospital-based IPFs, similar to the methodology used for the 2008-based RPL 
CMS-1627-P 42

market basket. We are proposing to determine the percent of total interest costs that are 

attributed to government and nonprofit IPFs separately for hospital-based and freestanding IPFs. 

We then are proposing to weight the nonprofit percentages for hospital-based and freestanding 

IPFs together using the proportion of total capital costs each provider type represents.

Table 3 below provides the detailed capital cost shares obtained from the Medicare cost 

reports. Ultimately, these detailed capital cost shares are applied to the total Capital-Related cost 

weight determined in section III.A.3.a.i to split out the total weight of 7.0 percent into more 

detailed cost categories and weights. 

Table 3.-Detailed Capital Cost Weights for the Proposed 2012-Based IPF Market Basket

Cost Shares Obtained from 

Medicare Cost Reports

Proposed Detailed Capital 

Cost Shares after Allocation of 

Lease Expenses

Depreciation 64% 75%

Building and Fixed 

Equipment 46% 53%

Movable Equipment 19% 22%

Interest 15% 17%

Government/Nonprofit 12% 14%

For Profit 2% 3%

Lease 15% n/a

Other 6% 8%

v. Proposed 2012-based IPF Market Basket Cost Categories and Weights

Table 4 below shows the cost categories and weights for the proposed 2012-based IPF 

market basket compared to the 2008-based RPL market basket.

Table 4-Proposed 2012-based IPF Cost Weights Compared to 2008-based RPL Cost Weights
CMS-1627-P 43

Cost Category

Proposed

2012-

based 

IPF Cost 

Weight

2008-based 

RPL Cost 

Weight

Total 100.0 100.0

 Compensation 65.2 62.3

 Wages and Salaries 51.9 49.4

 Employee Benefits 13.3 12.8

 Utilities 1.8 1.6

 Electricity 0.8 1.1

 Fuel, Oil, and Gasoline 0.9 0.4

 Water & Sewerage 0.1 0.1

 Professional Liability Insurance 1.1 0.8

 Malpractice 1.1 0.8

 All Other Products and Services 25.0 27.0

 All Other Products 11.7 15.6

 Pharmaceuticals 4.8 6.5

 Food: Direct Purchases 1.4 3.0

 Food: Contract Services 0.9 0.4

 Chemicals 0.6 1.1

 Medical Instruments 1.9 1.8

 Rubber & Plastics 0.5 1.1

 Paper and Printing Products 1.0 1.0

 Apparel - 0.2

 Machinery and Equipment - 0.1

 Miscellaneous Products 0.7 0.3

 All Other Services 13.3 11.4

 Labor-Related Services 6.7 4.7

 Professional Fees: Labor-related 2.9 2.1

 Administrative and Facilities Support Services 0.7 0.4

 Installation, Maintenance, and Repair 1.6 -

 All Other: Labor-related Services 1.5 2.1

 Nonlabor-Related Services 6.6 6.7

 Professional Fees: Nonlabor-related 2.6 4.2

 Financial services 2.3 0.9

 Telephone Services 0.6 0.4

 Postage - 0.6

 All Other: Nonlabor-related Services 1.1 0.6

 Capital-Related Costs 7.0 8.4

 Depreciation 5.2 5.5

 Fixed Assets 3.7 3.3
CMS-1627-P 44

 Movable Equipment 1.5 2.2

 Interest Costs 1.2 2.0

 Government/Nonprofit 1.0 0.7

 For Profit 0.2 1.3

 Other Capital-Related Costs 0.6 0.9

 Other Capital-Related Costs 0.6 0.9

The proposed 2012-based IPF market basket does not include separate cost categories for 

Apparel, Machinery & Equipment, and Postage. Due to the small weights associated with these 

detailed categories and relatively stable price growth in the applicable price proxy, we are 

proposing to include Apparel and Machinery & Equipment in the Miscellaneous Products cost 

category and Postage in the All-Other Nonlabor-related Services. We note that these Machinery 

& Equipment expenses are for equipment that is paid for in a given year and not depreciated over 

the assets’ useful life. Depreciation expenses for movable equipment are reflected in the Capitalrelated costs of the proposed 2012-based IPF market basket. For the proposed 2012-based IPF 

market basket, we are also proposing to include a separate cost category for Installation, 

Maintenance, and Repair. 

b. Selection of Price Proxies

After developing the cost weights for the proposed 2012-based IPF market basket, we 

selected the most appropriate wage and price proxies currently available to represent the rate of 

price change for each expenditure category. For the majority of the cost weights, we base the 

price proxies on Bureau of Labor Statistics (BLS) data and group them into one of the following 

BLS categories:

 Employment Cost Indexes. Employment Cost Indexes (ECIs) measure the rate of 

change in employment wage rates and employer costs for employee benefits per hour worked. 

These indexes are fixed-weight indexes and strictly measure the change in wage rates and 

employee benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) as price 
CMS-1627-P 45

proxies for input price indexes because they are not affected by shifts in occupation or industry 

mix, and because they measure pure price change and are available by both occupational group 

and by industry. The industry ECIs are based on the North American Classification System 

(NAICS) and the occupational ECIs are based on the Standard Occupational Classification 

System (SOC). 

 Producer Price Indexes. Producer Price Indexes (PPIs) measure price changes for 

goods sold in other than retail markets. PPIs are used when the purchases of goods or services 

are made at the wholesale level.

 Consumer Price Indexes. Consumer Price Indexes (CPIs) measure change in the 

prices of final goods and services bought by consumers. CPIs are only used when the purchases 

are similar to those of retail consumers rather than purchases at the wholesale level, or if no 

appropriate PPIs are available.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, 

and relevance:

 Reliability. Reliability indicates that the index is based on valid statistical methods and has 

low sampling variability. Widely accepted statistical methods ensure that the data were collected 

and aggregated in a way that can be replicated. Low sampling variability is desirable because it 

indicates that the sample reflects the typical members of the population. (Sampling variability is 

variation that occurs by chance because only a sample was surveyed rather than the entire 

population.) 

 Timeliness. Timeliness implies that the proxy is published regularly, preferably at least once 

a quarter. The market baskets are updated quarterly and, therefore, it is important for the 

underlying price proxies to be up-to-date, reflecting the most recent data available. We believe 
CMS-1627-P 46

that using proxies that are published regularly (at least quarterly, whenever possible) helps to 

ensure that we are using the most recent data available to update the market basket. We strive to 

use publications that are disseminated frequently, because we believe that this is an optimal way 

to stay abreast of the most current data available. 

 Availability. Availability means that the proxy is publicly available. We prefer that our

proxies are publicly available because this will help ensure that our market basket updates are as 

transparent to the public as possible. In addition, this enables the public to be able to obtain the 

price proxy data on a regular basis. 

 Relevance. Relevance means that the proxy is applicable and representative of the cost 

category weight to which it is applied. The CPIs, PPIs, and ECIs that we have selected to 

propose in this regulation meet these criteria. Therefore, we believe that they continue to be the 

best measure of price changes for the cost categories to which they would be applied.

Table 6 lists all price proxies for the proposed 2012-based IPF market basket. Below is a 

detailed explanation of the price proxies we are proposing for each cost category weight.

i. Price Proxies for the Operating Portion of the Proposed 2012-Based IPF Market Basket

Wages and Salaries

To measure wage price growth in the proposed 2012-based IPF market basket, we are 

proposing to apply a proxy blend based on six occupational subcategories within the Wages and 

Salaries category, which would reflect the IPF occupational mix. There is not a published wage 

proxy for IPF workers. The 2008-based RPL market basket uses the ECI for Wages and Salaries 

for All Civilian workers in Hospitals (BLS series code #CIU1026220000000I) to proxy these 

expenses. 

We propose to use the National Industry-Specific Occupational Employment and Wage 
CMS-1627-P 47

estimates for North American Industrial Classification System (NAICS) 622200, Psychiatric & 

Substance Abuse Hospitals, published by the BLS Office of Occupational Employment Statistics 

(OES), as the data source for the wage cost shares in the wage proxy blend. We propose to use 

OES’ May 2012 data. Detailed information on the methodology for the national industryspecific occupational employment and wage estimates survey can be found at 

http://www.bls.gov/oes/current/oes_tec.htm.

Based on the OES data, there are six wage subcategories: Management; NonHealth

Professional and Technical; Health Professional and Technical; Health Service; NonHealth 

Service; and Clerical. Table 5 lists the proposed 2012 occupational assignments for the six wage 

subcategories. 

 TABLE 5: Proposed 2012 Occupational Assignments for IPF Wage Blend

2012 Proposed Occupational Groupings

Group 1 Management

11-0000 Management Occupations

Group 2 NonHealth Professional & Technical

13-0000 Business and Financial Operations Occupations

15-0000 Computer and Mathematical Science Occupations

17-0000 Architecture and Engineering Occupations

19-0000 Life, Physical, and Social Science Occupations

23-0000 Legal Occupations

25-0000 Education, Training, and Library Occupations

27-0000 Arts, Design, Entertainment, Sports, and Media Occupations

Group 3 Health Professional & Technical

29-1021 Dentists, General

29-1031 Dietitians and Nutritionists

29-1051 Pharmacists

29-1062 Family and General Practitioners

29-1063 Internists, General

29-1069 Physicians and Surgeons, All Other

29-1071 Physician Assistants

29-1111 Registered Nurses

29-1122 Occupational Therapists

29-1123 Physical Therapists
CMS-1627-P 48

29-1125 Recreational Therapists

29-1126 Respiratory Therapists

29-1127 Speech-Language Pathologists

29-1129 Therapists, All Other

29-1199 Health Diagnosing and Treating Practitioners, All Other

Group 4 Health Service

21-0000 Community and Social Services Occupations

29-2011 Medical and Clinical Laboratory Technologists

29-2012 Medical and Clinical Laboratory Technicians

29-2021 Dental Hygienists

29-2032 Diagnostic Medical Sonographers

29-2034 Radiologic Technologists and Technicians

29-2041 Emergency Medical Technicians and Paramedics

29-2051 Dietetic Technicians

29-2052 Pharmacy Technicians

29-2054 Respiratory Therapy Technicians

29-2061 Licensed Practical and Licensed Vocational Nurses

29-2071 Medical Records and Health Information Technicians

29-2099 Health Technologists and Technicians, All Other

29-9012 Occupational Health and Safety Technicians

29-9099 Healthcare Practitioner and Technical Workers, All Other

31-0000 Healthcare Support Occupations

Group 5 NonHealth Service 

33-0000 Protective Service Occupations

35-0000 Food Preparation and Serving Related Occupations

37-0000 Building and Grounds Cleaning and Maintenance Occupations

39-0000 Personal Care and Service Occupations

41-0000 Sales and Related Occupations

47-0000 Construction and Extraction Occupations

49-0000 Installation, Maintenance, and Repair Occupations

51-0000 Production Occupations

53-0000 Transportation and Material Moving Occupations

Group 6 Clerical

43-0000 Office and Administrative Support Occupations

Total expenditures by occupation (i.e., occupational assignment) were calculated by 

taking the OES number of employees multiplied by the OES annual average salary. These

expenditures were aggregated based on the six groups in Table 6. We next calculated the 

proportion of each group’s expenditures relative to the total expenditures of all six groups. 
CMS-1627-P 49

These proportions, listed in Table 5, represent the weights used in the wage proxy blend. We 

propose using the published wage proxies in Table 6 for each of the six groups (that is, wage 

subcategories) as we believe these six price proxies are the most technically appropriate indices 

available to measure the price growth of the Wages and Salaries cost category in the proposed 

2012-based IPF market basket.

TABLE 6: Proposed 2012-Based IPF Market Basket Wage Proxy Blend

A comparison of the yearly changes from FY 2012 to FY 2015 for the proposed 2012-

based IPF wage blend and the 2008-based RPL wage proxy is shown in Table 7. The average 

annual increase in the 2 price proxies is similar, and in no year is the difference greater than 0.2 

percentage point.

Wage 

Subcategory

Wage Blend 

Weight Price Proxy BLS Series ID

Health Service 36.2

ECI for Wages and Salaries for All 

Civilian workers in Healthcare and Social 

Assistance

CIU1026200000000I

Health

Professional and 

Technical

33.5 ECI for Wages and Salaries for All 

Civilian workers in Hospitals

CIU1026220000000I

NonHealth Service 9.2 ECI for Wages and Salaries for Private 

Industry workers in Service Occupations CIU2020000300000I

NonHealth

Professional and 

Technical

7.3

ECI for Wages and Salaries for Private 

Industry workers in Professional, 

Scientific, and Technical Services

CIU2025400000000I

Management 7.1

ECI for Wages and Salaries for Private 

Industry workers in Management, 

Business, and Financial

CIU2020000110000I

Clerical 6.7

ECI for Wages and Salaries for Private 

Industry workers in Office and 

Administrative Support

CIU2020000220000I

(a) T

o

t

a

l

100.0 Total
CMS-1627-P 50

TABLE 7: Fiscal Year Growth in the Proposed 2012-based IPF Wage Proxy Blend and 

2008-based RPL Wage Proxy

2012 2013 2014 2015

Average 

2012- 2015

2012-based IPF Proposed Wage Proxy Blend 1.6 1.6 1.6 2.2 1.8

2008-based RPL Wage Proxy 1.5 1.5 1.5 2.0 1.6

 **Source: IHS Global Insight, Inc., 1st Quarter 2015 forecast with historical data through 4

th Quarter 2014

Benefits

For measuring benefits price growth in the proposed 2012-based IPF market basket, we 

are proposing to apply a benefits proxy blend based on the same six subcategories and the same 

six blend weights proposed for the wage proxy blend. These subcategories and blend weights 

are listed in Table 8. 

Applicable benefit ECIs, that are identical in industry definition to the wage blend ECIs, 

were selected for each of the six subcategories. These proposed benefit ECIs, listed in Table 8, 

are not publically available. Therefore, we calculated “ECIs for Total Benefits” using publically 

available “ECIs for Total Compensation” for each subcategory and the relative importance of 

wages within that subcategory’s total compensation. This is the same benefits ECI methodology 

we implemented in our IPPS, SNF, HHA, RPL, LTCH, and ESRD market baskets. We believe 

the six price proxies listed in Table 8 are the most technically appropriate indices to measure the 

price growth of the Benefits cost category in the proposed 2012-based IPF market basket. 

The current 2008-based RPL market basket uses the ECI for Benefits for All Civilian 

Workers in Hospitals to proxy Benefit expenses.
CMS-1627-P 51

TABLE 8: Proposed 2012-Based IPF Market Basket Benefits Proxy Blend

Wage Subcategory

Wage 

Blend 

Weight

Price Proxy

Health Service 36.2

ECI for Total Benefits for All Civilian 

workers in Healthcare and Social 

Assistance

Health Professional and 

Technical 33.5 ECI for Total Benefits for All Civilianworkers in Hospitals

NonHealth Service 9.2 ECI for Total Benefits for Private 

Industry workers in Service Occupations

NonHealth Professional and 

Technical 7.3

ECI for Total Benefits for Private 

Industry workers in Professional, 

Scientific, and Technical Services

Management 7.1

ECI for Total Benefits for Private 

Industry workers in Management, 

Business, and Financial

Clerical 6.7

ECI for Total Benefits for Private 

Industry workers in Office and

Administrative Support

(b) T

o

t

a

l

100.0

A comparison of the yearly changes from FY 2012 to FY 2015 for the proposed 2012-

based IPF benefit proxy blend and the 2008-based RPL benefit proxy is shown in Table 9. The 

average annual increase in the 2 price proxies is similar, and in no year is the difference greater 

than 0.4 percentage point. 

TABLE 9: Fiscal Year Growth in the Proposed 2012-based IPF Benefit 

Proxy Blend and 2008-based RPL Benefit Proxy

2012 2013 2014 2015

Average 

2012- 2015

2012-based IPF Proposed Benefit Proxy Blend 2.5 1.9 2.0 2.2 2.2

2008-based RPL Benefit Proxy 2.1 1.8 2.1 2.1 2.0

Source: IHS Global Insight, Inc., 1

st Quarter 2015 forecast with historical data through 4th Quarter 2014

Electricity

We are proposing to continue to use the PPI for Commercial Electric Power (BLS series 

code #WPU0542) to measure the price growth of this cost category. This is the same price proxy 

used in the 2008-based RPL market basket. 

Total
CMS-1627-P 52

Fuel, Oil, and Gasoline

We are proposing to change the proxy used for the Fuel, Oil, and Gasoline cost category. 

The 2008-based RPL market basket uses the PPI for Petroleum Refineries (BLS series code 

#PCU32411-32411) to proxy these expenses. 

For the proposed 2012-based IPF market basket, we are proposing to use a blend of the 

PPI for Petroleum Refineries and the PPI Commodity for Natural Gas (BLS series code 

#WPU0531). Our analysis of the Bureau of Economic Analysis’ 2007 Benchmark Input-Output

data (use table before redefinitions, purchaser’s value for NAICS 622000 [Hospitals]), shows 

that Petroleum Refineries expenses accounts for approximately 70 percent and Natural Gas 

accounts for approximately 30 percent of the Fuel, Oil, and Gasoline expenses. Therefore, we 

propose a blend using 70 percent of the PPI for Petroleum Refineries (BLS series code 

#PCU32411-32411) and 30 percent of the PPI Commodity for Natural Gas (BLS series code 

#WPU0531). We believe that these 2 price proxies are the most technically appropriate indices

available to measure the price growth of the Fuel, Oil, and Gasoline cost category in the 

proposed 2012-based IPF market basket. 

Water and Sewerage

We are proposing to continue to use the CPI for Water and Sewerage Maintenance (BLS 

series code #CUUR0000SEHG01) to measure the price growth of this cost category. This is the 

same proxy used in the 2008-based RPL market basket.

Professional Liability Insurance

We are proposing to continue to use the CMS Hospital Professional Liability Index to 

measure changes in professional liability insurance (PLI) premiums. To generate this index, we

collect commercial insurance premiums for a fixed level of coverage while holding non-price 
CMS-1627-P 53

factors constant (such as a change in the level of coverage). This is the same proxy used in the

2008-based RPL market basket.

Pharmaceuticals

We are proposing to continue to use the PPI for Pharmaceuticals for Human Use,

Prescription (BLS series code #WPUSI07003) to measure the price growth of this cost category. 

This is the same proxy used in the 2008-based RPL market basket.

Food: Direct Purchases

We are proposing to continue to use the PPI for Processed Foods and Feeds (BLS series

code #WPU02) to measure the price growth of this cost category. This is the same proxy used in 

the 2008-based RPL market basket.

Food: Contract Purchases

We are proposing to continue to use the CPI for Food Away From Home (BLS series 

code #CUUR0000SEFV) to measure the price growth of this cost category. This is the same

proxy used in the 2008-based RPL market basket.

Chemicals

We are proposing to continue to use a four part blended PPI composed of the PPI for 

Industrial Gas Manufacturing (BLS series code PCU325120325120P), the PPI for Other Basic 

Inorganic Chemical Manufacturing (BLS series code #PCU32518-32518), the PPI for Other 

Basic Organic Chemical Manufacturing (BLS series code #PCU32519-32519), and the PPI for 

Soap and Cleaning Compound Manufacturing (BLS series code #PCU32561-32561). We 

propose updating the blend weights using 2007 Benchmark I-O data which, compared to 2002 

Benchmark I-O data, is weighted more toward organic chemical products and weighted less 

toward inorganic chemical products. 
CMS-1627-P 54

Table 10 below shows the proposed weights for each of the four PPIs used to create the 

blended PPI. These are the same four proxies used in the 2008-based RPL market basket; 

however, the blended PPI weights in the 2008-based RPL market baskets were based on 2002 

Benchmark I-O data.

TABLE 10: Blended Chemical PPI Weights

Name

Proposed

2012-based IPF 

Weights

2008-based 

RPL 

Weights

NAICS

PPI for Industrial Gas Manufacturing 32% 35% 325120

PPI for Other Basic Inorganic Chemical Manufacturing 17% 25% 325180

PPI for Other Basic Organic Chemical Manufacturing 45% 30% 325190

PPI for Soap and Cleaning Compound Manufacturing 6% 10% 325610

Medical Instruments

We are proposing to use a blend for the Medical Instruments cost category. The 2007 

Benchmark Input-Output data shows an approximate 50/50 split between Surgical and Medical 

Instruments and Medical and Surgical Appliances and Supplies for this cost category. Therefore, 

we propose a blend composed of 50 percent of the commodity-based PPI for Surgical and 

Medical Instruments (BLS code #WPU1562) and 50 percent of the commodity-based PPI for 

Medical and Surgical Appliances and Supplies (BLS code #WPU1563). The 2008-based RPL 

market basket uses the single, higher level PPI for Medical, Surgical, and Personal Aid Devices

(BLS series code #WPU156).

Rubber and Plastics

We are proposing to continue to use the PPI for Rubber and Plastic Products (BLS series 

code #WPU07) to measure price growth of this cost category. This is the same proxy used in the 

2008-based RPL market basket.

Paper and Printing Products
CMS-1627-P 55

We are proposing to continue to use the PPI for Converted Paper and Paperboard 

Products (BLS series code #WPU0915) to measure the price growth of this cost category. This

is the same proxy used in the 2008-based RPL market basket.

Miscellaneous Products

We are proposing to continue to use the PPI for Finished Goods Less Food and Energy (BLS 

series code #WPUSOP3500) to measure the price growth of this cost category. This is the same 

proxy used in the 2008-based RPL market basket.

Professional Fees: Labor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry 

workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the 

price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Administrative and Facilities Support Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry 

workers in Office and Administrative Support (BLS series code #CIU2010000220000I ) to 

measure the price growth of this category. This is the same proxy used in the 2008-based RPL 

market basket.

Installation, Maintenance, and Repair

We are proposing to use the ECI for Total Compensation for Civilian workers in 

Installation, Maintenance, and Repair (BLS series code #CIU1010000430000I ) to measure the 

price growth of this new cost category. Previously these costs were included in the All Other: 

Labor-related Services category and were proxied by the ECI for Total Compensation for Private 

Industry workers in Service Occupations (BLS series code #CIU2010000300000I). We believe 
CMS-1627-P 56

that this index better reflects the price changes of labor associated with maintenance-related 

services and its incorporation represents a technical improvement to the market basket.

All Other: Labor-Related Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry 

workers in Service Occupations (BLS series code #CIU2010000300000I) to measure the price 

growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Fees: Nonlabor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry 

workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the 

price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Financial Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry 

workers in Financial Activities (BLS series code #CIU201520A000000I) to measure the price 

growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Telephone Services

We are proposing to continue to use the CPI for Telephone Services (BLS series code 

#CUUR0000SEED) to measure the price growth of this cost category. This is the same proxy 

used in the 2008-based RPL market basket.

All Other: Nonlabor-Related Services

We are proposing to continue to use the CPI for All Items Less Food and Energy (BLS 

series code #CUUR0000SA0L1E) to measure the price growth of this cost category. This is the 

same proxy used in the 2008-based RPL market basket.

ii. Price Proxies for the Capital Portion of the Proposed 2012-Based IPF Market Basket

Capital Price Proxies Prior to Vintage Weighting
CMS-1627-P 57

We are proposing to apply the same price proxies to the detailed capital-related cost 

categories as were applied in the 2008-based RPL market basket, which are provided in Table 12 

and described below. We are also proposing to continue to vintage weight the capital price 

proxies for Depreciation and Interest in order to capture the long-term consumption of capital. 

This vintage weighting method is similar to the method used for the 2008-based RPL market 

basket and is described below.

We are proposing to proxy the Depreciation: Building and Fixed Equipment cost 

category by BEA's Chained Price Index for Nonresidential Construction for Hospitals and 

Special Care Facilities (BEA Table 5.4.4. Price Indexes for Private Fixed Investment in 

Structures by Type). We are proposing to proxy the Depreciation: Movable Equipment cost 

category by the PPI for Machinery and Equipment (BLS series code #WPU11). We are 

proposing to proxy the Nonprofit Interest cost category by the average yield on domestic 

municipal bonds (Bond Buyer 20-bond index). We are proposing to proxy the For-profit Interest 

cost category by the average yield on Moody's Aaa bonds (Federal Reserve). We are proposing 

to proxy the Other Capital-Related cost category by the CPI-U for Rent of Primary Residence 

(BLS series code #CUUS0000SEHA). We believe these are the most appropriate proxies for 

IPF capital-related costs that meet our selection criteria of relevance, timeliness, availability, and 

reliability.

Vintage Weights for Price Proxies

Because capital is acquired and paid for over time, capital-related expenses in any given 

year are determined by both past and present purchases of physical and financial capital. The 

vintage-weighted capital-related portion of the proposed 2012-based IPF market basket is 

intended to capture the long-term consumption of capital, using vintage weights for depreciation 
CMS-1627-P 58

(physical capital) and interest (financial capital). These vintage weights reflect the proportion of 

capital-related purchases attributable to each year of the expected life of building and fixed 

equipment, movable equipment, and interest. We are proposing to use vintage weights to 

compute vintage-weighted price changes associated with depreciation and interest expenses.

Capital-related costs are inherently complicated and are determined by complex 

capital-related purchasing decisions, over time, based on such factors as interest rates and debt 

financing. In addition, capital is depreciated over time instead of being consumed in the same 

period it is purchased. By accounting for the vintage nature of capital, we are able to provide an 

accurate and stable annual measure of price changes. Annual non-vintage price changes for 

capital are unstable due to the volatility of interest rate changes and, therefore, do not reflect the 

actual annual price changes for IPF capital-related costs. The capital-related component of the 

proposed 2012-based IPF market basket reflects the underlying stability of the capital-related 

acquisition process.

To calculate the vintage weights for depreciation and interest expenses, we first need a 

time series of capital-related purchases for building and fixed equipment and movable 

equipment. We found no single source that provides an appropriate time series of capital-related 

purchases by hospitals for all of the above components of capital purchases. The early Medicare 

cost reports did not have sufficient capital-related data to meet this need. Data we obtained from 

the American Hospital Association (AHA) do not include annual capital-related purchases. 

However, the AHA does provide a consistent database of total expenses back to 1963. 

Consequently, we are proposing to use data from the AHA Panel Survey and the AHA Annual 

Survey to obtain a time series of total expenses for hospitals. We are then proposing to use data 

from the AHA Panel Survey supplemented with the ratio of depreciation to total hospital 
CMS-1627-P 59

expenses obtained from the Medicare cost reports to derive a trend of annual depreciation 

expenses for 1963 through 2012. We propose to separate these depreciation expenses into 

annual amounts of building and fixed equipment depreciation and movable equipment 

depreciation as determined above. From these annual depreciation amounts we derive annual 

end-of-year book values for building and fixed equipment and movable equipment using the 

expected life for each type of asset category. While data are not available that are specific to 

IPFs, we believe this information for all hospitals serves as a reasonable alternative for the 

pattern of depreciation for IPFs. 

To continue to calculate the vintage weights for depreciation and interest expenses, we 

also need the expected lives for Building and Fixed Equipment, Movable Equipment, and 

Interest for the proposed 2012-based IPF market basket. We are proposing to calculate the 

expected lives using Medicare cost report data from freestanding and hospital-based IPFs. The 

expected life of any asset can be determined by dividing the value of the asset (excluding fully 

depreciated assets) by its current year depreciation amount. This calculation yields the estimated 

expected life of an asset if the rates of depreciation were to continue at current year levels, 

assuming straight-line depreciation. We are proposing to determine the expected life of building 

and fixed equipment separately for hospital-based IPFs and freestanding IPFs and weight these 

expected lives using the percent of total capital costs each provider type represents. We are 

proposing to apply a similar method for movable equipment. Using these proposed methods, we 

determined the average expected life of building and fixed equipment to be equal to 23 years, 

and the average expected life of movable equipment to be equal to 11 years. For the expected 

life of interest, we believe vintage weights for interest should represent the average expected life 

of building and fixed equipment because, based on previous research described in the FY 1997 
CMS-1627-P 60

IPPS final rule (61 FR 46198), the expected life of hospital debt instruments and the expected 

life of buildings and fixed equipment are similar. We note that for the 2008-based RPL market 

basket, we used FY 2008 Medicare cost reports for IPPS hospitals to determine the expected life 

of building and fixed equipment and movable equipment (76 FR 51763). The 2008-based RPL 

market basket was based on an expected average life of building and fixed equipment of 26 years 

and an expected average life of movable equipment of 11 years, which were both calculated 

using data for IPPS hospitals. 

Multiplying these expected lives by the annual depreciation amounts results in annual 

year-end asset costs for building and fixed equipment and movable equipment. We then 

calculate a time series, beginning in 1964, of annual capital purchases by subtracting the 

previous year’s asset costs from the current year’s asset costs. 

For the building and fixed equipment and movable equipment vintage weights, we are 

proposing to use the real annual capital-related purchase amounts for each asset type to capture 

the actual amount of the physical acquisition, net of the effect of price inflation. These real 

annual capital-related purchase amounts are produced by deflating the nominal annual purchase 

amount by the associated price proxy as provided above. For the interest vintage weights, we are 

proposing to use the total nominal annual capital-related purchase amounts to capture the value 

of the debt instrument (including, but not limited to, mortgages and bonds). Using these 

capital-related purchase time series specific to each asset type, we are proposing to calculate the 

vintage weights for building and fixed equipment, for movable equipment, and for interest. 

The vintage weights for each asset type are deemed to represent the average purchase 

pattern of the asset over its expected life (in the case of building and fixed equipment and 

interest, 23 years, and in the case of movable equipment, 11 years). For each asset type, we used 
CMS-1627-P 61

the time series of annual capital-related purchase amounts available from 2012 back to 1964. 

These data allow us to derive twenty-seven 23-year periods of capital-related purchases for 

building and fixed equipment and interest, and thirty-nine 11-year periods of capital-related 

purchases for movable equipment. For each 23-year period for building and fixed equipment 

and interest, or 11-year period for movable equipment, we calculate annual vintage weights by 

dividing the capital-related purchase amount in any given year by the total amount of purchases 

over the entire 23-year or 11-year period. This calculation is done for each year in the 23-year or 

11-year period and for each of the periods for which we have data. We then calculate the 

average vintage weight for a given year of the expected life by taking the average of these 

vintage weights across the multiple periods of data. The vintage weights for the capital-related 

portion of the 2008-based RPL market basket and the proposed 2012-based IPF market basket 

are presented in Table 11 below.

Table 11: 2008-Based RPL market basket and Proposed 2012-based IPF market basket Vintage 

Weights for Capital-Related Price Proxies

Year

Building and Fixed 

Equipment

Movable Equipment Interest

2012-based 

23 years

2008-based 

26 years

2012-

based

11 years

2008-

based

11 years

2012-

based

23 years

2008-

based

26 years

1 0.029 0.021 0.069 0.071 0.017 0.010 

2 0.031 0.023 0.073 0.075 0.019 0.012 

3 0.034 0.025 0.077 0.080 0.022 0.014 

4 0.036 0.027 0.083 0.083 0.024 0.016 

5 0.037 0.028 0.087 0.085 0.026 0.018 

6 0.039 0.030 0.091 0.089 0.028 0.020 

7 0.040 0.031 0.096 0.092 0.030 0.021 

8 0.041 0.033 0.100 0.098 0.032 0.024 

9 0.042 0.035 0.103 0.103 0.035 0.026 

10 0.044 0.037 0.107 0.109 0.038 0.029 

11 0.045 0.039 0.114 0.116 0.040 0.033 

12 0.045 0.041 -- -- 0.042 0.035 

13 0.045 0.042 -- -- 0.044 0.038 

14 0.046 0.043 -- -- 0.046 0.041 

15 0.046 0.044 -- -- 0.048 0.043 
CMS-1627-P 62

Year

Building and Fixed 

Equipment

Movable Equipment Interest

2012-based 

23 years

2008-based 

26 years

2012-

based

11 years

2008-

based

11 years

2012-

based

23 years

2008-

based

26 years

16 0.048 0.045 -- -- 0.053 0.046 

17 0.049 0.046 -- -- 0.057 0.049 

18 0.050 0.047 -- -- 0.060 0.052 

19 0.051 0.047 -- -- 0.063 0.053 

20 0.051 0.045 -- -- 0.066 0.053 

21 0.051 0.045 -- -- 0.067 0.055 

22 0.050 0.045 -- -- 0.069 0.056 

23 0.052 0.046 -- -- 0.073 0.060

24 -- 0.046 -- -- -- 0.063

25 -- 0.045 -- -- -- 0.064

26 -- 0.046 -- -- -- 0.068

Total 1.000 1.000 1.000 1.000 1.000 1.000

Note: Numbers may not add to total due to rounding.

The process of creating vintage-weighted price proxies requires applying the vintage 

weights to the price proxy index where the last applied vintage weight in Table 11 is applied to 

the most recent data point. We have provided on the CMS Web site an example of how the 

vintage weighting price proxies are calculated, using example vintage weights and example price 

indices. The example can be found at the following link: http://www.cms.gov/ResearchStatistics-Data-and-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/MarketBasketResearch.html in the zip file titled “Weight 

Calculations as described in the IPPS FY 2010 Proposed Rule.”

iii. Summary of Price Proxies of the Proposed 2012-Based IPF Market Basket

Table 12 shows both the operating and capital price proxies for the proposed 2012-based 

IPF Market Basket.
CMS-1627-P 63

 TABLE 12: Price Proxies for the Proposed 2012-based IPF Market Basket

Cost Description Price Proxies Weight

(percent)

Total 100.0

 Compensation 65.2

 Wages and Salaries Blended Wages and Salaries Price Proxy 51.9

 Employee Benefits Blended Benefits Price Proxy 13.3

 Utilities 1.8

 Electricity PPI for Commercial Electric Power 0.8

 Fuel, Oil, and Gasoline

Blend of the PPI for Petroleum Refineries and PPI for 

Natural Gas 0.9

 Water & Sewerage CPI-U for Water and Sewerage Maintenance 0.1

 Professional Liability Insurance 1.1

 Malpractice

CMS Hospital Professional Liability Insurance Premium 

Index 1.1

 All Other Products and Services 25.0

 All Other Products 11.7

 Pharmaceuticals PPI for Pharmaceuticals for human use, prescription 4.8

 Food: Direct Purchases PPI for Processed Foods and Feeds 1.4

 Food: Contract Services CPI-U for Food Away From Home 0.9

 Chemicals Blend of Chemical PPIs 0.6

 Medical Instruments

Blend of the PPI for Surgical and medical instruments and 

PPI for Medical and surgical appliances and supplies 1.9

 Rubber & Plastics PPI for Rubber and Plastic Products 0.5

 Paper and Printing Products PPI for Converted Paper and Paperboard Products 1.0

 Miscellaneous Products PPI for Finished Goods Less Food and Energy 0.7

 All Other Services 13.3

 Labor-Related Services 6.7

 Professional Fees: Labor-related

ECI for Total compensation for Private industry workers in 

Professional and related 2.9

 Administrative and Facilities 

Support Services

ECI for Total compensation for Private industry workers in 

Office and administrative support 0.7

 Installation, Maintenance, and Repair

ECI for Total compensation for Civilian workers in 

Installation, maintenance, and repair 1.6

 All Other: Labor-related Services

ECI for Total compensation for Private industry workers in 

Service occupations 1.5

 Nonlabor-Related Services 6.6

 Professional Fees: Nonlabor-related

ECI for Total compensation for Private industry workers in 

Professional and related 2.6

 Financial services

ECI for Total compensation for Private industry workers in 

Financial activities 2.3

 Telephone Services CPI-U for Telephone Services 0.6

 All Other: Nonlabor-related Services CPI-U for All Items Less Food and Energy 1.1

 Capital-Related Costs 7.0

 Depreciation 5.2

 Fixed Assets

BEA chained price index for nonresidential construction for 

hospitals and special care facilities - vintage weighted (23 

years) 3.7

 Movable Equipment

PPI for machinery and equipment - vintage weighted (11 

years) 1.5

 Interest Costs 1.2
CMS-1627-P 64

 Government/Nonprofit

Average yield on domestic municipal bonds (Bond Buyer 20 

bonds) - vintage weighted (23 years) 1.0

 For Profit

Average yield on Moody's Aaa bonds - vintage weighted (23 

years) 0.2

 Other Capital-Related Costs CPI-U for Rent of primary residence 0.6

 Note: Totals may not sum to 100.0 percent due to rounding

4. Proposed FY 2016 Market Basket Update

For FY 2016 (that is, beginning October 1, 2015 and ending September 30, 2016), we are 

proposing to use an estimate of the proposed 2012-based IPF market basket increase factor to 

update the IPF PPS base payment rate. Consistent with historical practice, we estimate the 

market basket update for the IPF PPS based on IHS Global Insight’s forecast using the most 

recent available data. IHS Global Insight (IGI), Inc. is a nationally recognized economic and 

financial forecasting firm that contracts with CMS to forecast the components of the market 

baskets and multifactor productivity (MFP).

Based on IGI’s first quarter 2015 forecast with historical data through the fourth quarter 

of 2014, the projected proposed 2012-based IPF market basket increase factor for FY 2016 is 2.7

percent. Therefore, consistent with our historical practice of estimating market basket increases 

based on the best available data, we are proposing a market basket increase factor of 2.7 percent

for FY 2016. We are also proposing that if more recent data are subsequently available (for 

example, a more recent estimate of the market basket) we would use such data, to determine the 

FY 2016 update in the final rule.

For comparison, the current 2008-based RPL market basket is projected to increase by 

2.8 percent in FY 2016 based on IGI’s first quarter 2015 forecast. Table 13 compares the 

proposed 2012-based IPF market basket and the 2008-based RPL market basket percent changes. 
CMS-1627-P 65

 TABLE 13: Proposed 2012-Based IPF Market basket and 2008-Based RPL Market Basket 

 Percent Changes, FY 2010 through FY 2018

Fiscal Year (FY)

Proposed 2012-

Based IPF Market 

Basket Index 

Percent Change

2008-Based RPL 

Market Basket Index 

Percent Change

Historical data:

 FY 2010 2.0 2.2

 FY 2011 2.2 2.5

 FY 2012 1.9 2.2

 FY 2013 2.0 2.1

 FY 2014 1.9 1.8

 Average 2010-2014 2.0 2.2

Forecast:

 FY 2015 2.0 2.2

 FY 2016 2.7 2.8

 FY 2017 3.0 3.0

 FY 2018 3.0 3.1

 Average 2015-2018 2.7 2.8

 Note: These market basket percent changes do not include any further adjustments as may be statutorily 

 required. Source: IHS Global Insight, Inc. 1st quarter 2015 forecast.

For FY 2016, the proposed 2012-based IPF market basket update (2.7 percent) is one 

tenth of a percentage point lower than the 2008-based RPL market basket (2.8 percent). The 0.1

percentage point difference stems from the lower Pharmaceuticals cost weight in the proposed 

2012-based IPF market basket (4.8 percent) compared to the 2008-based RPL market basket (6.5 

percent) as well as from the use of the blended price proxies for the Wages and Salaries and 

Employee Benefits cost categories. 

5. Proposed Productivity Adjustment 

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity 

adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the RY 

beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. The statute 

defines the productivity adjustment to be equal to the 10-year moving average of changes in 

annual economy-wide private nonfarm business multifactor productivity (MFP) (as projected by 

the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or 

other annual period) (the “MFP adjustment”). The Bureau of Labor Statistics (BLS) publishes 
CMS-1627-P 66

the official measure of private non-farm business MFP. We refer readers to the BLS web site at 

http://www.bls.gov/mfp for the BLS historical published MFP data. 

MFP is derived by subtracting the contribution of labor and capital inputs growth from 

output growth. The projections of the components of MFP are currently produced by IGI, a 

nationally recognized economic forecasting firm with which CMS contracts to forecast the 

components of the market baskets and MFP. As described in the FY 2012 IPPS/LTCH final rule 

(76 FR 51690 through 51692), in order to generate a forecast of MFP, IGI replicated the MFP 

measure calculated by the BLS using a series of proxy variables derived from IGI’s U.S. 

macroeconomic models. In the FY 2012 rule, we identified each of the major MFP component 

series employed by the BLS to measure MFP as well as provided the corresponding concepts 

determined to be the best available proxies for the BLS series.

Beginning with the FY 2016 rulemaking cycle, the MFP adjustment is calculated using a 

revised series developed by IGI to proxy the aggregate capital inputs. Specifically, IGI has 

replaced the Real Effective Capital Stock used for Full Employment GDP with a forecast of BLS 

aggregate capital inputs recently developed by IGI using a regression model. This series 

provides a better fit to the BLS capital inputs, as measured by the differences between the actual 

BLS capital input growth rates and the estimated model growth rates over the historical time 

period. Therefore, we are using IGI’s most recent forecast of the BLS capital inputs series in the 

MFP calculations beginning with the FY 2016 rulemaking cycle. A complete description of the 

MFP projection methodology is available on our website at http://www.cms.gov/ResearchStatistics-Data-and-Systems/Statistics-Trends-andReports/MedicareProgramRatesStats/MarketBasketResearch.html. Although we discuss the IGI 

changes to the MFP proxy series in this proposed rule, in the future, when IGI makes changes to 
CMS-1627-P 67

the MFP methodology, we will announce them on our website rather than in the annual 

rulemaking.

Using IGI’s first quarter 2015 forecast, the MFP adjustment for FY 2016 (the 10-year 

moving average of MFP for the period ending FY 2016) is projected to be 0.6 percent. Thus, in 

accordance with section 1886(s)(2)(A)(i) of the Act, we propose to base the FY 2016 market 

basket update, which is used to determine the applicable percentage increase for the IPF 

payments, on the most recent estimate of the proposed 2012-based IPF market basket (currently 

estimated to be 2.7 percent based on IGI’s first quarter 2015 forecast). We propose to then 

reduce this percentage increase by the current estimate of the MFP adjustment for FY 2016 of 

0.6 percentage point (the 10-year moving average of MFP for the period ending FY 2016 based 

on IGI’s first quarter 2015 forecast). Furthermore, we also propose that if more recent data are 

subsequently available (for example, a more recent estimate of the market basket and MFP 

adjustment), we would use such data to determine the FY 2016 market basket update and MFP 

adjustment in the final rule. 

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that 

reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the 

Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 

2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2 

percentage point. We are proposing to implement the productivity adjustment and ‘other 

adjustment’ in this FY 2016 IPF PPS proposed rule. We invite public comment on these 

proposals.

6. Proposed Labor-related Share

Due to variations in geographic wage levels and other labor-related costs, we believe that 
CMS-1627-P 68

payment rates under the IPF PPS should continue to be adjusted by a geographic wage index, 

which would apply to the labor-related portion of the Federal per diem base rate (hereafter 

referred to as the labor-related share). The labor-related share is determined by identifying the 

national average proportion of total costs that are related to, influenced by, or vary with the local 

labor market. We continue to classify a cost category as labor-related if the costs are laborintensive and vary with the local labor market. As stated in the FY 2015 IPF PPS final rule (79 

FR 45943), the labor-related share was defined as the sum of the relative importance of Wages 

and Salaries, Employee Benefits, Professional Fees: Labor- Related Services, Administrative 

and Facilities Support Services, All Other: Labor-related Services, and a portion of the Capital 

Costs from the 2008-based RPL market basket.

Based on our definition of the labor-related share and the cost categories in the proposed 

2012-based IPF market basket, we are proposing to include in the labor-related share the sum of 

the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: LaborRelated, Administrative and Facilities Support Services, Installation, Maintenance, and Repair, 

All Other: Labor-related Services, and a portion of the Capital-Related cost weight from the 

proposed 2012-based IPF market basket. As noted in Section III.A.3.b.i of this proposed rule, 

for the proposed 2012-based IPF market basket, we have created a separate cost category for 

Installation, Maintenance and Repair services. These expenses were previously included in the 

“All Other” Labor-related Services cost category in the 2008-based RPL market basket, along 

with other services, including but not limited to janitorial, waste management, security, and dry 

cleaning / laundry services. Because these services tend to be labor-intensive and are mostly 

performed at the facility (and, therefore, unlikely to be purchased in the national market), we 

continue to believe that they meet our definition of labor-related services.
CMS-1627-P 69

Similar to the 2008-based RPL market basket, the proposed 2012-based IPF market 

basket includes 2 cost categories for nonmedical Professional fees (including but not limited to, 

expenses for legal, accounting, and engineering services). These are Professional Fees: Laborrelated and Professional Fees: Nonlabor-related. For the proposed 2012-based IPF market 

basket, we propose to estimate the labor-related percentage of non-medical professional fees 

(and assign these expenses to the Professional Fees: Labor-related services cost category) based 

on the same method that was used to determine the labor-related percentage of professional fees 

in the 2008-based RPL market basket. 

To summarize, the professional services survey found that hospitals purchase the 

following proportion of these four services outside of their local labor market: 

• 34 percent of accounting and auditing services.

• 30 percent of engineering services.

• 33 percent of legal services.

• 42 percent of management consulting services.

We applied each of these percentages to the respective Benchmark I–O cost category 

underlying the professional fees cost category to determine the Professional Fees: Nonlaborrelated costs. The Professional Fees: Labor-related costs were determined to be the difference 

between the total costs for each Benchmark I–O category and the Professional Fees: Nonlaborrelated costs. This is the same methodology that we used to separate the 2008-based RPL market 

basket professional fees category into Professional Fees: Labor-related and Professional Fees: 

Nonlabor-related cost categories. For more detail regarding this methodology see the FY 2012 

IPF final rule (76 FR 26445). 

In addition to the professional services listed above, we also classified expenses under 
CMS-1627-P 70

NAICS 55, Management of Companies and Enterprises, into the Professional Fees cost category 

as was done in the 2008-based RPL market basket. The NAICS 55 data are mostly comprised of 

corporate, subsidiary, and regional managing offices, or otherwise referred to as home offices. 

Since many facilities are not located in the same geographic area as their home office, we 

analyzed data from a variety of sources in order to determine what proportion of these costs 

should be appropriately included in the labor-related share. For the 2012-based IPF market 

basket, we are proposing to derive the home office percentages using data for both freestanding 

IPF providers and hospital-based IPF providers. In the 2008-based RPL market basket, we used 

the home office percentages based on the data reported by freestanding IRFs, IPFs, and LTCHs. 

Using data primarily from the Medicare cost reports and the Home Office Medicare Records 

(HOMER) database that provides the address (including city and state) for home offices, we 

were able to determine that 36 percent of the total number of freestanding and hospital-based 

IPFs that had home offices had those home offices located in their respective local labor 

markets—defined as being in the same Metropolitan Statistical Area (MSA).

The Medicare cost report requires hospitals to report their home office provider numbers. 

Using the HOMER database to determine the home office location for each home office provider 

number, we compared the location of the provider with the location of the hospital’s home 

office. We then placed providers into one of the following 2 groups:

• Group 1—Provider and home office are located in different MSAs.

• Group 2—Provider and home office are located in the same MSA.

We found that 64 percent of the providers with home offices were classified into Group 1 

(that is, different MSA) and, thus, these providers were determined to not be located in the same 

local labor market as their home office. We found that 36 percent of all providers with home 
CMS-1627-P 71

offices were classified into Group 2 (that is, the same MSA). Given these results, we are 

proposing to classify 36 percent of the Professional Fees costs into the Professional Fees: Laborrelated cost category and the remaining 64 percent into the Professional Fees: Nonlabor-related 

Services cost category. This methodology for apportioning the Professional Fee expenses 

between labor-related and nonlabor-related categories is similar to the method used in the 2008-

based RPL market basket (see 76 FR 26445). 

Using this proposed method and the IHS Global Insight, Inc. 4th quarter 2014 forecast for 

the proposed 2012-based IPF market basket, the proposed IPF labor-related share for FY 2016 is 

the sum of the FY 2016 relative importance of each labor-related cost category. The relative 

importance reflects the different rates of price change for these cost categories between the base 

year (FY 2012) and FY 2016. Table 14 shows the proposed FY 2016 labor-related share using 

the proposed 2012-based IPF market basket relative importance and the FY 2015 labor-related 

share using the 2008-based RPL market basket.

The sum of the relative importance for FY 2016 operating costs (Wages and Salaries, 

Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support 

Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services) is 

71.8 percent, as shown in Table 14. We are proposing to specify the labor-related share to one 

decimal place, which is consistent with the IPPS labor-related share (currently the Labor-related 

share from the RPL market basket is specified to 3 decimal places).

We are proposing that the portion of Capital that is influenced by the local labor market is 

estimated to be 46 percent, which is the same percentage applied to the 2008-based RPL market 

basket. Since the relative importance for Capital-Related Costs is 6.8 percent of the proposed 

2012-based IPF market basket in FY 2016, we are proposing to take 46 percent of 6.8 percent to 
CMS-1627-P 72

determine the proposed labor-related share of Capital for 2016. The result would be 3.1 percent, 

which we propose to add to 71.8 percent for the operating cost amount to determine the total 

proposed labor-related share for FY 2016.

The FY 2016 labor-related share using the proposed 2012-based IPF market basket is 

about five percentage points higher than the FY 2015 labor-related share using the 2008-based 

RPL market basket. Of the five percentage point difference, 3 percentage points is attributable to 

the higher Wages and Salaries and Employee Benefits cost weights in the 2012-based IPF market 

basket compared to the 2008-based RPL market basket, while 2 percentage points is attributable 

to the higher weight associated with the labor-related services cost categories. We would note 

that the higher Wages and Salaries cost weight in the 2012-based IPF market basket relative to 

the 2008-based RPL market basket is the result of freestanding IPFs having a larger percentage 

of costs attributable to labor than freestanding IRFs and Long-term care hospitals. These latter 

facilities were included in the 2008-based RPL market basket. 

Table 14: Proposed 2016 IPF Labor-Related Share

FY 2016 Laborrelated Share based 

on Proposed 2012-

based IPF Market 

Basket1

FY 2015 

Final Laborrelated 

Share2

Wages and Salaries 51.7 48.271

Employee Benefits 13.4 12.936

Professional Fees: Labor-related 2.9 2.058

Administrative and Facilities

Support Services 0.7 0.415

Installation, Maintenance and 

Repair 1.6-

All Other: Labor-related Services 1.5 2.061

Subtotal 71.8 65.741

Labor-related portion of capital 

(46%) 3.1 3.553

Total LRS 74.9 69.294

1

IHS Global Insight, Inc. 4th quarter 2014 forecast.

2Federal Register 79-FR-45943
CMS-1627-P 73

In weighing the effects of the change in the LRS, we considered whether to recommend a 

2-year transitional implementation of the increase in the LRS. We recognize that IPFs with wage 

index values of less than one would be adversely affected by an increased LRS, as a larger share 

of the base rate would be adjusted by the wage index value. About 69 percent of IPFs would 

have wage index values of less than one using FY2015 CBSA data, and 30 percent of these 

providers are rural. While the LRS would be updated in a budget neutral fashion so that the 

overall impact on payments is zero, there would still be distributional effects on specific 

categories of IPFs. We considered the distributional effects of the multiple proposals made in 

this proposed rule, including the proposal to update the full LRS in FY 2016, and we found that 

the negative impact of updating the LRS in a single year, without a transition, was relatively 

small, as shown in Table 26 in section VII. of this proposed rule. Additionally, we are proposing 

2 other adjustments to benefit providers: a transitional wage index and a phase-out of the 17 

percent rural adjustment for the 37 IPFs that would change from rural to urban status due to the 

new CBSA delineations. As presented in section III.A.6. of this proposed rule, we are 

proposing to use the 2012-based IPF market basket relative importance’s to determine the FY

2016 IPF LRS. We believe this is technically appropriate as it is based on more recent, providerspecific data for IPFs. For all of these reasons, we propose to implement the full LRS in FY 

2016, but solicit comments on this issue.

B. Proposed Updates to the IPF PPS for FY 2016 (Beginning October 1, 2015)

The IPF PPS is based on a standardized Federal per diem base rate calculated from the 

IPF average per diem costs and adjusted for budget-neutrality in the implementation year. The 

Federal per diem base rate is used as the standard payment per day under the IPF PPS and is 

adjusted by the patient-level and facility-level adjustments that are applicable to the IPF stay. A 
CMS-1627-P 74

detailed explanation of how we calculated the average per diem cost appears in the November 

2004 IPF PPS final rule (69 FR 66926). 

1. Determining the Standardized Budget-Neutral Federal Per Diem Base Rate 

Section 124(a)(1) of the BBRA required that we implement the IPF PPS in a budgetneutral manner. In other words, the amount of total payments under the IPF PPS, including any 

payment adjustments, must be projected to be equal to the amount of total payments that would 

have been made if the IPF PPS were not implemented. Therefore, we calculated the 

budget-neutrality factor by setting the total estimated IPF PPS payments to be equal to the total 

estimated payments that would have been made under the Tax Equity and Fiscal Responsibility 

Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A 

step-by-step description of the methodology used to estimate payments under the TEFRA 

payment system appears in the November 2004 IPF PPS final rule (69 FR 66926). 

Under the IPF PPS methodology, we calculated the final Federal per diem base rate to be 

budget-neutral during the IPF PPS implementation period (that is, the 18-month period from 

January 1, 2005 through June 30, 2006) using a July 1 update cycle. We updated the average 

cost per day to the midpoint of the IPF PPS implementation period (that is, October 1, 2005), and 

this amount was used in the payment model to establish the budget-neutrality adjustment. 

Next, we standardized the IPF PPS Federal per diem base rate to account for the overall 

positive effects of the IPF PPS payment adjustment factors by dividing total estimated payments 

under the TEFRA payment system by estimated payments under the IPF PPS. Additional 

information concerning this standardization can be found in the November 2004 IPF PPS final 

rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR 27045). We then reduced the 

standardized Federal per diem base rate to account for the outlier policy, the stop loss provision, 
CMS-1627-P 75

and anticipated behavioral changes. A complete discussion of how we calculated each 

component of the budget-neutrality adjustment appears in the November 2004 IPF PPS final rule 

(69 FR 66932 through 66933) and in the May 2006 IPF PPS final rule (71 FR 27044 through 

27046). The final standardized budget-neutral Federal per diem base rate established for cost 

reporting periods beginning on or after January 1, 2005 was calculated to be $575.95. 

The Federal per diem base rate has been updated in accordance with applicable statutory 

requirements and §412.428 through publication of annual notices or proposed and final rules. A 

detailed discussion on the standardized budget-neutral Federal per diem base rate and the 

electroconvulsive therapy (ECT) rate appears in the August 2013 IPF PPS update notice (78 FR 

46738 through 46739). These documents are available on the CMS website at 

http://www.cms.hhs.gov/InpatientPsychFacilPPS/.

2. Proposed FY 2016 Update of the Federal Per Diem Base Rate and Electroconvulsive Therapy 

(ECT) Rate

The current (that is, FY 2015) Federal per diem base rate is $728.31 and the ECT rate is 

$313.55. For FY 2016, we are proposing to apply an update of 1.9 percent (that is, the proposed 

FY 2012-based IPF-specific market basket increase for FY 2016 of 2.7 percent less the proposed

productivity adjustment of 0.6 percentage point, and further reduced by the 0.2 percentage point 

required under section1886(s)(3)(D) of the Act), and the wage index budget-neutrality factor of 

1.0041 (as discussed in section III.D.1.e. of this proposed rule) to the FY 2015 Federal per diem 

base rate of $728.31, yielding a proposed Federal per diem base rate of $745.19 for FY 2016. 

Similarly, we are proposing to apply the 1.9 percent payment update and the 1.0041 wage index 

budget-neutrality factor to the FY 2015 ECT rate, yielding a proposed ECT rate of $320.82 for

FY 2016.
CMS-1627-P 76

As noted above, section 1886(s)(4) of the Act requires the establishment of a quality data 

reporting program for the IPF PPS beginning in RY 2015. We refer readers to section V. of this 

proposed rule for a discussion of the IPF Quality Reporting Program. Section 1886(s)(4)(A)(i) 

of the Act requires that, for RY 2014 and each subsequent rate year, the Secretary shall reduce 

any annual update to a standard Federal rate for discharges occurring during the rate year by 2.0 

percentage points for any IPF that does not comply with the quality data submission 

requirements with respect to an applicable year. Therefore, we are proposing to apply a 2.0 

percentage point reduction to the Federal per diem base rate and the ECT rate as follows: 

For IPFs that failed to submit quality reporting data under the IPFQR program, we would

apply a -0.1 percent annual update (that is, 1.9 percent reduced by 2 percentage points, in 

accordance with section 1886(s)(4)(A)(ii) of the Act) and the wage index budget-neutrality factor 

of 1.0041 to the FY 2015 Federal per diem base rate of $728.31, yielding a Federal per diem 

base rate of $730.56 for FY 2016. 

Similarly, we would apply the -0.1 percent annual update and the 1.0041 wage index 

budget-neutrality factor to the FY 2015 ECT rate of $313.55, yielding an ECT rate of $314.52

for FY 2016.

C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors

The IPF PPS payment adjustments were derived from a regression analysis of 100 

percent of the FY 2002 MedPAR data file, which contained 483,038 cases. For a more detailed 

description of the data file used for the regression analysis, see the November 2004 IPF PPS final 

rule (69 FR 66935 through 66936). While we have since used more recent claims data to

simulate payments to set the fixed dollar loss threshold amount for the outlier policy and to 
CMS-1627-P 77

assess the impact of the IPF PPS updates, we continue to use the regression-derived adjustment 

factors established in 2005 for FY 2016. 

2. IPF PPS Patient-Level Adjustments

The IPF PPS includes payment adjustments for the following patient-level characteristics:

Medicare Severity Diagnosis Related Groups (MS–DRGs) assignment of the patient’s principal 

diagnosis, selected comorbidities, patient age, and the variable per diem adjustments.

a. MS-DRG Assignment

We believe it is important to maintain the same diagnostic coding and DRG classification 

for IPFs that are used under the IPPS for providing psychiatric care. For this reason, when the 

IPF PPS was implemented for cost reporting periods beginning on or after January 1, 2005, we 

adopted the same diagnostic code set (ICD-9-CM) and DRG patient classification system (that is, 

the CMS DRGs) that were utilized at the time under the IPPS. In the May 2008 IPF PPS notice 

(73 FR 25709), we discussed CMS’s effort to better recognize resource use and the severity of 

illness among patients. CMS adopted the new MS-DRGs for the IPPS in the FY 2008 IPPS final 

rule with comment period (72 FR 47130). In the 2008 IPF PPS notice (73 FR 25716), we 

provided a crosswalk to reflect changes that were made under the IPF PPS to adopt the new MSDRGs. For a detailed description of the mapping changes from the original DRG adjustment 

categories to the current MS-DRG adjustment categories, we refer readers to the May 2008 IPF 

PPS notice (73 FR 25714).

The IPF PPS includes payment adjustments for designated psychiatric DRGs assigned to 

the claim based on the patient’s principal diagnosis. The DRG adjustment factors were 

expressed relative to the most frequently reported psychiatric DRG in FY 2002, that is, DRG 430 

(psychoses). The coefficient values and adjustment factors were derived from the regression 
CMS-1627-P 78

analysis. Mapping the DRGs to the MS-DRGs resulted in the current 17 IPF-MS-DRGs, instead 

of the original 15 DRGs, for which the IPF PPS provides an adjustment. 

For the FY 2016 update, we are not proposing any changes to the IPF MS-DRG 

adjustment factors. In FY 2015 rulemaking (79 FR 45945 through 45947), we proposed and 

finalized conversions of the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, 

which will be implemented on October 1, 2015. Further information for the ICD-10-CM/PCS

MS-DRG conversion project can be found on the CMS ICD-10-CM web site at 

http://www.cms.hhs.gov/Medicare/Coding/ICD10/ICD-10-MS-DRG-Conversion-Project.html.

For FY 2016, we propose to continue to make a payment adjustment for psychiatric 

diagnoses that group to one of the existing 17 MS-IPF-DRGs listed in the Addendum. 

Psychiatric principal diagnoses that do not group to one of the 17 designated DRGs would still 

receive the Federal per diem base rate and all other applicable adjustments, but the payment 

would not include a DRG adjustment.

As noted above, the diagnoses for each IPF MS-DRG will be updated on October 1,

2015, using the ICD-10-CM/PCS code sets. 

b. Payment for Comorbid Conditions 

The intent of the comorbidity adjustments is to recognize the increased costs associated 

with comorbid conditions by providing additional payments for certain concurrent medical or 

psychiatric conditions that are expensive to treat. In the May 2011 IPF PPS final rule (76 FR 

26451 through 26452), we explained that the IPF PPS includes 17 comorbidity categories and 

identified the new, revised, and deleted ICD-9-CM diagnosis codes that generate a comorbid 

condition payment adjustment under the IPF PPS for RY 2012 (76 FR 26451). 

Comorbidities are specific patient conditions that are secondary to the patient’s principal 
CMS-1627-P 79

diagnosis and that require treatment during the stay. Diagnoses that relate to an earlier episode 

of care and have no bearing on the current hospital stay are excluded and must not be reported on 

IPF claims. Comorbid conditions must exist at the time of admission or develop subsequently, 

and affect the treatment received, length of stay (LOS), or both treatment and LOS.

For each claim, an IPF may receive only one comorbidity adjustment within a 

comorbidity category, but it may receive an adjustment for more than one comorbidity category. 

Current billing instructions for claims for discharges on or after October 1, 2015 require IPFs to

enter the complete ICD-10-CM codes for up to 24 additional diagnoses if they co-exist at the 

time of admission, or develop subsequently and impact the treatment provided. 

The comorbidity adjustments were determined based on the regression analysis using the 

diagnoses reported by IPFs in FY 2002. The principal diagnoses were used to establish the DRG 

adjustments and were not accounted for in establishing the comorbidity category adjustments, 

except where ICD-9-CM “code first” instructions apply. As we explained in the May 2011 IPF 

PPS final rule (76 FR 265451), the “code first” rule applies when a condition has both an 

underlying etiology and a manifestation due to the underlying etiology. For these conditions, 

ICD-9-CM has a coding convention that requires the underlying conditions to be sequenced first 

followed by the manifestation. Whenever a combination exists, there is a “use additional code” 

note at the etiology code and a “code first” note at the manifestation code.

The same principle holds for ICD-10-CM as for ICD-9-CM. Whenever a combination 

exists, there is a “use additional code” note in the ICD-10-CM codebook pertaining to the 

etiology code, and a “code first” code pertaining to the manifestation code. In the FY 2015 IPF 

PPS final rule, we provided a “code first” table for reference that highlights the same or similar 

manifestation codes where the “code first” instructions apply in ICD-10-CM that were present in 
CMS-1627-P 80

ICD-9-CM (79 FR 46009). 

As noted previously, it is our policy to maintain the same diagnostic coding set for IPFs 

that is used under the IPPS for providing the same psychiatric care. The 17 comorbidity 

categories formerly defined using ICD-9-CM codes were converted to ICD-10-CM/PCS in the 

FY 2015 IPF PPS final rule (79 FR 45947 to 45955). The goal for converting the comorbidity 

categories is referred to as replication, meaning that the payment adjustment for a given patient 

encounter is the same after ICD-10-CM implementation as it would be if the same record had 

been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation on 

October 1, 2015. All conversion efforts were made with the intent of achieving this goal. 

We are not proposing any refinements to the comorbidity adjustments at this time, and 

propose to continue to use the existing adjustments in effect in FY 2015. The FY 2016 

comorbidity adjustments are found in the Addendum to this proposed rule.

3. Patient Age Adjustments

As explained in the November 2004 IPF PPS final rule (69 FR 66922), we analyzed the 

impact of age on per diem cost by examining the age variable (that is, the range of ages) for 

payment adjustments. In general, we found that the cost per day increases with age. The older 

age groups are more costly than the under 45 age group, the differences in per diem cost increase 

for each successive age group, and the differences are statistically significant. 

For FY 2016, we are proposing to continue to use the patient age adjustments currently in 

effect in FY 2015, as shown in the Addendum to this proposed rule. 

4. Variable Per Diem Adjustments

We explained in the November 2004 IPF PPS final rule (69 FR 66946) that the regression 

analysis indicated that per diem cost declines as the LOS increases. The variable per diem 
CMS-1627-P 81

adjustments to the Federal per diem base rate account for ancillary and administrative costs that 

occur disproportionately in the first days after admission to an IPF. 

We used a regression analysis to estimate the average differences in per diem cost among 

stays of different lengths. As a result of this analysis, we established variable per diem 

adjustments that begin on day 1 and decline gradually until day 21 of a patient's stay. For day 22 

and thereafter, the variable per diem adjustment remains the same each day for the remainder of 

the stay. However, the adjustment applied to day 1 depends upon whether the IPF has a 

qualifying emergency department (ED). If an IPF has a qualifying ED, it receives a 1.31 

adjustment factor for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 

1.19 adjustment factor for day 1 of the stay. The ED adjustment is explained in more detail in 

section III.D.4. of this proposed rule. 

For FY 2016, we propose to continue to use the variable per diem adjustment factors 

currently in effect as shown in the Addendum to this proposed rule. A complete discussion of 

the variable per diem adjustments appears in the November 2004 IPF PPS final rule (69 FR 

66946). 

D. Proposed Updates to the IPF PPS Facility-Level Adjustments 

The IPF PPS includes facility-level adjustments for the wage index, IPFs located in rural 

areas, teaching IPFs, cost of living adjustments for IPFs located in Alaska and Hawaii, and IPFs 

with a qualifying ED. 

1. Proposed Wage Index Adjustment 

a. Background 

As discussed in the May 2006 IPF PPS final rule (71 FR 27061) and in the May 2008 (73 

FR 25719) and May 2009 IPF PPS notices (74 FR 20373), in order to provide an adjustment for 
CMS-1627-P 82

geographic wage levels, the labor-related portion of an IPF's payment is adjusted using an 

appropriate wage index. Currently, an IPF's geographic wage index value is determined based 

on the actual location of the IPF in an urban or rural area as defined in §412.64(b)(1)(ii)(A) and 

(C). 

b. Proposed Wage Index for FY 2016

Since the inception of the IPF PPS, we have used the pre-floor, pre-reclassified acute care 

hospital wage index in developing a wage index to be applied to IPFs because there is not an 

IPF-specific wage index available. We believe that IPFs generally compete in the same labor 

markets as acute care hospitals, so the pre-floor, pre-reclassified hospital wage index should 

reflect IPF labor costs. As discussed in the May 2006 IPF PPS final rule for FY 2007 (71 FR 

27061 through 27067), under the IPF PPS, the wage index is calculated using the IPPS wage 

index for the labor market area in which the IPF is located, without taking into account 

geographic reclassifications, floors, and other adjustments made to the wage index under the 

IPPS. For a complete description of these IPPS wage index adjustments, please see the CY 2013 

IPPS/LTCH PPS final rule (77 FR 53365 through 53374). For FY 2016, we are proposing to

continue to apply the most recent hospital wage index (that is, the FY 2015 pre-floor, prereclassified hospital wage index, which is the most appropriate index as it best reflects the 

variation in local labor costs of IPFs in the various geographic areas) using the most recent 

hospital wage data (that is, data from hospital cost reports for the cost reporting period beginning 

during FY 2011) without any geographic reclassifications, floors, or other adjustments. We 

propose to apply the FY 2016 IPF PPS wage index to payments beginning October 1, 2015.

We apply the wage index adjustment to the labor-related portion of the Federal rate, 

which we are proposing to change from 69.294 percent to 74.9 percent in FY 2016. This 
CMS-1627-P 83

percentage reflects the labor-related relative importance of the FY 2012-based proposed IPFspecific market basket for FY 2016 (see section III.A.6. of this proposed rule). 

c. OMB Bulletins and Proposed Transitional Wage Index

OMB publishes bulletins regarding CBSA changes, including changes to CBSA numbers 

and titles. In the May 2006 IPF PPS final rule for RY 2007 (71 FR 27061 through 27067), we 

adopted the changes discussed in the Office of Management and Budget (OMB) Bulletin No. 

03-04 (June 6, 2003), which announced revised definitions for Metropolitan Statistical Areas 

(MSAs), and the creation of Micropolitan Statistical Areas and Combined Statistical Areas. In 

adopting the OMB CBSA geographic designations in RY 2007, we did not provide a separate 

transition for the CBSA-based wage index since the IPF PPS was already in a transition period 

from TEFRA payments to PPS payments. 

In the May 2008 IPF PPS notice, we incorporated the CBSA nomenclature changes 

published in the most recent OMB bulletin that applies to the hospital wage index used to 

determine the current IPF PPS wage index and stated that we expect to continue to do the same 

for all the OMB CBSA nomenclature changes in future IPF PPS rules and notices, as necessary 

(73 FR 25721). The OMB bulletins may be accessed online at 

http://www.whitehouse.gov/omb/bulletins_default/.

In accordance with our established methodology, we have historically adopted any CBSA 

changes that are published in the OMB bulletin that corresponds with the hospital wage index 

used to determine the IPF PPS wage index. For the FY 2015 IPF wage index, we used the FY 

2014 pre-floor, pre-reclassified hospital wage index to adjust the IPF PPS payments. On

February 28, 2013, OMB issued OMB Bulletin No. 13-01, which established revised 

delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined 
CMS-1627-P 84

Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. 

A copy of this bulletin may be obtained at http://www.whitehouse.gov/omb/bulletins_default/. 

Because the FY 2014 pre-floor, pre-reclassified hospital wage index was finalized prior to the 

issuance of this Bulletin, the FY 2015 IPF PPS wage index, which was based on the FY 2014

pre-floor, pre-reclassified hospital wage index, did not reflect OMB’s new area delineations 

based on the 2010 Census. According to OMB, “[t]his bulletin provides the delineations of all 

Metropolitan Statistical Areas, Metropolitan Divisions, Micropolitan Statistical Areas, Combined 

Statistical Areas, and New England City and Town Areas in the United States and Puerto Rico 

based on the standards published on June 28, 2010, in the Federal Register (75 FR 37246 

through 37252) and Census Bureau data.” These OMB Bulletin changes are reflected in the FY 

2015 pre-floor, pre-reclassified hospital wage index, upon which the FY 2016 IPPS PPS wage 

index is based. We propose to adopt these new OMB CBSA delineations in the FY 2016 

proposed IPF PPS wage index. 

We believe that the most current CBSA delineations accurately reflect the local 

economies and wage levels of the areas where IPFs are located, and we believe that it is 

important for the IPF PPS to use the latest CBSA delineations available in order to maintain an 

up-to-date payment system that accurately reflects the reality of population shifts and labor 

market conditions. 

In proposing adoption of these changes for the IPF PPS, it is necessary to identify the 

new labor market area delineation for each county and facility in the country. For example, there 

would be new CBSAs, urban counties that would become rural, rural counties that would 

become urban, and existing CBSAs that would be split apart. Because the wage index of urban 

areas is typically higher than that of rural areas, IPF facilities currently located in rural counties 
CMS-1627-P 85

that would become urban, beginning October 1, 2015, would generally experience an increase in 

their wage index values. We identified 105 counties and 37 IPFs that would move from rural to 

urban status due to the new CBSA delineations beginning in FY 2016, shown in Table 15.

TABLE 15: FY 2016 RURAL to URBAN CBSA CROSSWALK

County Name

FY 2014 CBSA 

Delineations/ FY 2015 

data

FY 2015 CBSA 

Delineations/ FY 2015 data

Change 

in value 

(percent) CBSA Urban/ 

Rural

Wage 

Index CBSA Urban/ Rural

Wage 

Index

Baldwin County, Alabama 1 RURAL 0.6963 19300 URBAN 0.7248 4.09%

Pickens County, Alabama 1 RURAL 0.6963 46220 URBAN 0.8337 19.73%

Cochise County, Arizona 3 RURAL 0.9125 43420 URBAN 0.8937 -2.06%

Little River County, 

Arkansas 4 RURAL 0.7311 45500 URBAN 0.7362 0.70%

Windham County, 

Connecticut 7 RURAL 1.1251 49340 URBAN 1.1493 2.15%

Sussex County, Delaware 8 RURAL 1.0261 41540 URBAN 0.9289 -9.47%

Citrus County, Florida 10 RURAL 0.8006 26140 URBAN 0.7625 -4.76%

Gulf County, Florida 10 RURAL 0.8006 37460 URBAN 0.7906 -1.25%

Highlands County, Florida 10 RURAL 0.8006 42700 URBAN 0.7982 -0.30%

Sumter County, Florida 10 RURAL 0.8006 45540 URBAN 0.8095 1.11%

Walton County, Florida 10 RURAL 0.8006 18880 URBAN 0.8156 1.87%

Lincoln County, Georgia 11 RURAL 0.7425 12260 URBAN 0.9225 24.24%

Morgan County, Georgia 11 RURAL 0.7425 12060 URBAN 0.9369 26.18%

Peach County, Georgia 11 RURAL 0.7425 47580 URBAN 0.7542 1.58%

Pulaski County, Georgia 11 RURAL 0.7425 47580 URBAN 0.7542 1.58%

Kalawao County, Hawaii 12 RURAL 1.0741 27980 URBAN 1.0561 -1.68%

Maui County, Hawaii 12 RURAL 1.0741 27980 URBAN 1.0561 -1.68%

Butte County, Idaho 13 RURAL 0.7398 26820 URBAN 0.8933 20.75%

De Witt County, Illinois 14 RURAL 0.8362 14010 URBAN 0.9165 9.60%

Jackson County, Illinois 14 RURAL 0.8362 16060 URBAN 0.8324 -0.45%

Williamson County, 

Illinois 14 RURAL 0.8362 16060 URBAN 0.8324 -0.45%

Scott County, Indiana 15 RURAL 0.8416 31140 URBAN 0.8605 2.25%

Union County, Indiana 15 RURAL 0.8416 17140 URBAN 0.9473 12.56%

Plymouth County, Iowa 16 RURAL 0.8451 43580 URBAN 0.8915 5.49%

Kingman County, Kansas 17 RURAL 0.7806 48620 URBAN 0.8472 8.53%

Allen County, Kentucky 18 RURAL 0.7744 14540 URBAN 0.8410 8.60%

Butler County, Kentucky 18 RURAL 0.7744 14540 URBAN 0.8410 8.60%

Acadia Parish, Louisiana 19 RURAL 0.7580 29180 URBAN 0.7869 3.81%

Iberia Parish, Louisiana 19 RURAL 0.7580 29180 URBAN 0.7869 3.81%
CMS-1627-P 86

St. James Parish, Louisiana 19 RURAL 0.7580 35380 URBAN 0.8821 16.37%

Tangipahoa Parish, 

Louisiana 19 RURAL 0.7580 25220 URBAN 0.9452 24.70%

Vermilion Parish, 

Louisiana 19 RURAL 0.7580 29180 URBAN 0.7869 3.81%

Webster Parish, Louisiana 19 RURAL 0.7580 43340 URBAN 0.8325 9.83%

St. Marys County, 

Maryland 21 RURAL 0.8554 15680 URBAN 0.8593 0.46%

Worcester County, 

Maryland 21 RURAL 0.8554 41540 URBAN 0.9289 8.59%

Midland County, Michigan 23 RURAL 0.8207 33220 URBAN 0.7935 -3.31%

Montcalm County, 

Michigan 23 RURAL 0.8207 24340 URBAN 0.8799 7.21%

Fillmore County, 

Minnesota 24 RURAL 0.9124 40340 URBAN 1.1398 24.92%

Le Sueur County, 

Minnesota 24 RURAL 0.9124 33460 URBAN 1.1196 22.71%

Mille Lacs County, 

Minnesota 24 RURAL 0.9124 33460 URBAN 1.1196 22.71%

Sibley County, Minnesota 24 RURAL 0.9124 33460 URBAN 1.1196 22.71%

Benton County, 

Mississippi 25 RURAL 0.7589 32820 URBAN 0.8991 18.47%

Yazoo County, Mississippi 25 RURAL 0.7589 27140 URBAN 0.7891 3.98%

Golden Valley County, 

Montana 27 RURAL 0.9024 13740 URBAN 0.8686 -3.75%

Hall County, Nebraska 28 RURAL 0.8924 24260 URBAN 0.9219 3.31%

Hamilton County, 

Nebraska 28 RURAL 0.8924 24260 URBAN 0.9219 3.31%

Howard County, Nebraska 28 RURAL 0.8924 24260 URBAN 0.9219 3.31%

Merrick County, Nebraska 28 RURAL 0.8924 24260 URBAN 0.9219 3.31%

Jefferson County, New 

York 33 RURAL 0.8208 48060 URBAN 0.8386 2.17%

Yates County, New York 33 RURAL 0.8208 40380 URBAN 0.8750 6.60%

Craven County, North 

Carolina 34 RURAL 0.7995 35100 URBAN 0.8994 12.50%

Davidson County, North 

Carolina 34 RURAL 0.7995 49180 URBAN 0.8679 8.56%

Gates County, North 

Carolina 34 RURAL 0.7995 47260 URBAN 0.9223 15.36%

Iredell County, North 

Carolina 34 RURAL 0.7995 16740 URBAN 0.9073 13.48%

Jones County, North 

Carolina 34 RURAL 0.7995 35100 URBAN 0.8994 12.50%

Lincoln County, North 

Carolina 34 RURAL 0.7995 16740 URBAN 0.9073 13.48%

Pamlico County, North 

Carolina 34 RURAL 0.7995 35100 URBAN 0.8994 12.50%

Rowan County, North 

Carolina 34 RURAL 0.7995 16740 URBAN 0.9073 13.48%

Oliver County, North 

Dakota 35 RURAL 0.7099 13900 URBAN 0.7216 1.65%
CMS-1627-P 87

Sioux County, North 

Dakota 35 RURAL 0.7099 13900 URBAN 0.7216 1.65%

Hocking County, Ohio 36 RURAL 0.8329 18140 URBAN 0.9539 14.53%

Perry County, Ohio 36 RURAL 0.8329 18140 URBAN 0.9539 14.53%

Cotton County, Oklahoma 37 RURAL 0.7799 30020 URBAN 0.7918 1.53%

Josephine County, Oregon 38 RURAL 1.0083 24420 URBAN 1.0086 0.03%

Linn County, Oregon 38 RURAL 1.0083 10540 URBAN 1.0879 7.89%

Adams County, 

Pennsylvania 39 RURAL 0.8719 23900 URBAN 1.0104 15.88%

Columbia County, 

Pennsylvania 39 RURAL 0.8719 14100 URBAN 0.9347 7.20%

Franklin County, 

Pennsylvania 39 RURAL 0.8719 16540 URBAN 1.0957 25.67%

Monroe County, 

Pennsylvania 39 RURAL 0.8719 20700 URBAN 0.9372 7.49%

Montour County, 

Pennsylvania 39 RURAL 0.8719 14100 URBAN 0.9347 7.20%

Utuado Municipio, Puerto 

Rico 40 RURAL 0.4047 10380 URBAN 0.3586 -11.39%

Beaufort County, South 

Carolina 42 RURAL 0.8374 25940 URBAN 0.8708 3.99%

Chester County, South 

Carolina 42 RURAL 0.8374 16740 URBAN 0.9073 8.35%

Jasper County, South 

Carolina 42 RURAL 0.8374 25940 URBAN 0.8708 3.99%

Lancaster County, South 

Carolina 42 RURAL 0.8374 16740 URBAN 0.9073 8.35%

Union County, South 

Carolina 42 RURAL 0.8374 43900 URBAN 0.8277 -1.16%

Custer County, South 

Dakota 43 RURAL 0.8312 39660 URBAN 0.8989 8.14%

Campbell County, 

Tennessee 44 RURAL 0.7365 28940 URBAN 0.7015 -4.75%

Crockett County, 

Tennessee 44 RURAL 0.7365 27180 URBAN 0.7747 5.19%

Maury County, Tennessee 44 RURAL 0.7365 34980 URBAN 0.8969 21.78%

Morgan County, Tennessee 44 RURAL 0.7365 28940 URBAN 0.7015 -4.75%

Roane County, Tennessee 44 RURAL 0.7365 28940 URBAN 0.7015 -4.75%

Falls County, Texas 45 RURAL 0.7855 47380 URBAN 0.8137 3.59%

Hood County, Texas 45 RURAL 0.7855 23104 URBAN 0.9386 19.49%

Hudspeth County, Texas 45 RURAL 0.7855 21340 URBAN 0.8139 3.62%

Lynn County, Texas 45 RURAL 0.7855 31180 URBAN 0.8830 12.41%

Martin County, Texas 45 RURAL 0.7855 33260 URBAN 0.8940 13.81%

Newton County, Texas 45 RURAL 0.7855 13140 URBAN 0.8508 8.31%

Oldham County, Texas 45 RURAL 0.7855 11100 URBAN 0.8277 5.37%

Somervell County, Texas 45 RURAL 0.7855 23104 URBAN 0.9386 19.49%

Box Elder County, Utah 46 RURAL 0.8891 36260 URBAN 0.9225 3.76%

Augusta County, Virginia 49 RURAL 0.7674 44420 URBAN 0.8326 8.50%

Buckingham County, 49 RURAL 0.7674 16820 URBAN 0.9053 17.97%
CMS-1627-P 88

Virginia

Culpeper County, Virginia 49 RURAL 0.7674 47894 URBAN 1.0403 35.56%

Floyd County, Virginia 49 RURAL 0.7674 13980 URBAN 0.8473 10.41%

Rappahannock County, 

Virginia 49 RURAL 0.7674 47894 URBAN 1.0403 35.56%

Staunton City County, 

Virginia 49 RURAL 0.7674 44420 URBAN 0.8326 8.50%

Waynesboro City County, 

Virginia 49 RURAL 0.7674 44420 URBAN 0.8326 8.50%

Columbia County, 

Washington 50 RURAL 1.0892 47460 URBAN 1.0934 0.39%

Pend Oreille County, 

Washington 50 RURAL 1.0892 44060 URBAN 1.1425 4.89%

Stevens County, 

Washington 50 RURAL 1.0892 44060 URBAN 1.1425 4.89%

Walla Walla County, 

Washington 50 RURAL 1.0892 47460 URBAN 1.0934 0.39%

Fayette County, West 

Virginia 51 RURAL 0.7410 13220 URBAN 0.8024 8.29%

Raleigh County, West 

Virginia 51 RURAL 0.7410 13220 URBAN 0.8024 8.29%

Green County, Wisconsin 52 RURAL 0.9041 31540 URBAN 1.1130 23.11%

The wage index values of rural areas are typically lower than that of urban areas. 

Therefore, IPFs located in a county that is currently designated as urban under the IPF PPS wage 

index that would become rural when we would adopt the new CBSA delineations may 

experience a decrease in their wage index values. We identified 37 counties and 3 IPFs that 

would move from urban to rural status due to the new CBSA delineations beginning in FY 2016. 

Table 16 shows the CBSA delineations and the urban wage index values for FY 2015 based on 

existing CBSA delineations, compared with the proposed CBSA delineations and wage index 

values for FY 2016 based on the new OMB CBSA delineations. Table 16 also shows the 

percentage change in these values for those counties that would change from urban to rural, 

beginning in FY 2016, when we would adopt the new CBSA delineations. 
CMS-1627-P 89

TABLE 16: FY 2016 URBAN to RURAL CBSA CROSSWALK

County Name

FY 2014 CBSA 

Delineations/ FY 2015 data

FY 2015 CBSA 

Delineations/ FY 2015 

data Change 

in value 

CBSA (percent) Urban/ 

Rural

Wage 

Index CBSA Urban/ Rural

Wage 

Index

Greene County, 

Alabama 46220 URBAN 0.8387 1 RURAL 0.6914 -17.56%

Franklin County, 

Arkansas 22900 URBAN 0.7593 4 RURAL 0.7311 -3.71%

Power County, Idaho 38540 URBAN 0.9672 13 RURAL 0.7398 -23.51%

Franklin County, Indiana 17140 URBAN 0.9473 15 RURAL 0.8416 -11.16%

Gibson County, Indiana 21780 URBAN 0.8537 15 RURAL 0.8416 -1.42%

Greene County, Indiana 14020 URBAN 0.9062 15 RURAL 0.8416 -7.13%

Tipton County, Indiana 29020 URBAN 0.8990 15 RURAL 0.8416 -6.38%

Franklin County, Kansas 28140 URBAN 0.9419 17 RURAL 0.7779 -17.41%

Geary County, Kansas 31740 URBAN 0.8406 17 RURAL 0.7779 -7.46%

Nelson County, 

Kentucky 31140 URBAN 0.8593 18 RURAL 0.7748 -9.83%

Webster County, 

Kentucky 21780 URBAN 0.8537 18 RURAL 0.7748 -9.24%

Franklin County, 

Massachusetts 44140 URBAN 1.0271 22 RURAL 1.1553 12.48%

Ionia County, Michigan 24340 URBAN 0.8965 23 RURAL 0.8288 -7.55%

Newaygo County, 

Michigan 24340 URBAN 0.8965 23 RURAL 0.8288 -7.55%

George County, 

Mississippi 37700 URBAN 0.7396 25 RURAL 0.7570 2.35%

Stone County, 

Mississippi 25060 URBAN 0.8179 25 RURAL 0.7570 -7.45%

Crawford County, 

Missouri 41180 URBAN 0.9366 26 RURAL 0.7725 -17.52%

Howard County, 

Missouri 17860 URBAN 0.8319 26 RURAL 0.7725 -7.14%

Washington County, 

Missouri 41180 URBAN 0.9366 26 RURAL 0.7725 -17.52%

Anson County, North 

Carolina 16740 URBAN 0.9230 34 RURAL 0.7899 -14.42%

Greene County, North 

Carolina 24780 URBAN 0.9371 34 RURAL 0.7899 -15.71%

Erie County, Ohio 41780 URBAN 0.7784 36 RURAL 0.8348 7.25%

Ottawa County, Ohio 45780 URBAN 0.9129 36 RURAL 0.8348 -8.56%

Preble County, Ohio 19380 URBAN 0.8938 36 RURAL 0.8348 -6.60%

Washington County, 

Ohio 37620 URBAN 0.8186 36 RURAL 0.8348 1.98%

Stewart County, 

Tennessee 17300 URBAN 0.7526 44 RURAL 0.7277 -3.31%

Calhoun County, Texas 47020 URBAN 0.8473 45 RURAL 0.7847 -7.39%

Delta County, Texas 19124 URBAN 0.9703 45 RURAL 0.7847 -19.13%
CMS-1627-P 90

San Jacinto County, 

Texas 26420 URBAN 0.9734 45 RURAL 0.7847 -19.39%

Summit County, Utah 41620 URBAN 0.9512 46 RURAL 0.9005 -5.33%

Cumberland County, 

Virginia 40060 URBAN 0.9625 49 RURAL 0.7554 -21.52%

Danville City County, 

Virginia 19260 URBAN 0.7963 49 RURAL 0.7554 -5.14%

King And Queen 

County, Virginia 40060 URBAN 0.9625 49 RURAL 0.7554 -21.52%

Louisa County, Virginia 40060 URBAN 0.9625 49 RURAL 0.7554 -21.52%

Pittsylvania County, 

Virginia 19260 URBAN 0.7963 49 RURAL 0.7554 -5.14%

Surry County, Virginia 47260 URBAN 0.9223 49 RURAL 0.7554 -18.10%

Morgan County, West 

Virginia 25180 URBAN 0.9080 51 RURAL 0.7274 -19.89%

Pleasants County, West 

Virginia 37620 URBAN 0.8186 51 RURAL 0.7274 -11.14%

We note that IPFs in some urban CBSAs would experience a change in their wage index 

values even though they remain urban because an urban CBSA’s boundaries and/or the counties 

included in that CBSA could change. Table 17 shows those counties that would experience a 

change in their wage index value in FY 2016 due to the new OMB CBSAs. Table 17 shows the 

urban CBSA delineations and wage index values for FY 2015 based on existing CBSA

delineations, compared with the urban CBSA delineations and wage index values for FY 2016

based on the new OMB delineations, and the percentage change in these values, for counties that 

would remain urban even though the CBSA boundaries and/or counties included in that CBSA 

would change.

TABLE 17: FY 2015 URBAN to a DIFFERENT FY 2016 URBAN CBSA CROSSWALK

County Name

FY 2014 CBSA 

Delineations/ FY 2015 data

FY 2015 CBSA 

Delineations/ FY 2015 data

Change 

in value 

(percent) CBSA Urban/ 

Rural

Wage 

Index CBSA Urban/ Rural

Wage 

Index

Flagler County, Florida 37380 URBAN 0.8462 19660 URBAN 0.8376 -1.02%

De Kalb County, Illinois 16974 URBAN 1.0412 20994 URBAN 1.0299 -1.09%

Kane County, Illinois 16974 URBAN 1.0412 20994 URBAN 1.0299 -1.09%

Madison County, Indiana 11300 URBAN 1.0078 26900 URBAN 1.0133 0.55%
CMS-1627-P 91

Meade County, Kentucky 31140 URBAN 0.8593 21060 URBAN 0.7701 -10.38%

Essex County, 

Massachusetts 37764 URBAN 1.0769 15764 URBAN 1.1159 3.62%

Ottawa County, Michigan 26100 URBAN 0.8136 24340 URBAN 0.8799 8.15%

Jackson County, 

Mississippi 37700 URBAN 0.7396 25060 URBAN 0.7896 6.76%

Bergen County, New 

Jersey 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Hudson County, New 

Jersey 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Middlesex County, New 

Jersey 20764 URBAN 1.0989 35614 URBAN 1.2837 16.82%

Monmouth County, New 

Jersey 20764 URBAN 1.0989 35614 URBAN 1.2837 16.82%

Ocean County, New 

Jersey 20764 URBAN 1.0989 35614 URBAN 1.2837 16.82%

Passaic County, New 

Jersey 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Somerset County, New 

Jersey 20764 URBAN 1.0989 35084 URBAN 1.1233 2.22%

Bronx County, New York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Dutchess County, New 

York 39100 URBAN 1.1533 20524 URBAN 1.1345 -1.63%

Kings County, New York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

New York County, New 

York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Orange County, New 

York 39100 URBAN 1.1533 35614 URBAN 1.2837 11.31%

Putnam County, New 

York 35644 URBAN 1.3110 20524 URBAN 1.1345 -13.46%

Queens County, New 

York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Richmond County, New 

York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Rockland County, New 

York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Westchester County, New 

York 35644 URBAN 1.3110 35614 URBAN 1.2837 -2.08%

Brunswick County, North 

Carolina 48900 URBAN 0.8867 34820 URBAN 0.8620 -2.79%

Bucks County, 

Pennsylvania 37964 URBAN 1.0837 33874 URBAN 1.0157 -6.27%

Chester County, 

Pennsylvania 37964 URBAN 1.0837 33874 URBAN 1.0157 -6.27%

Montgomery County, 

Pennsylvania 37964 URBAN 1.0837 33874 URBAN 1.0157 -6.27%

Arecibo Municipio, 

Puerto Rico 41980 URBAN 0.4449 11640 URBAN 0.4213 -5.30%

Camuy Municipio, Puerto 

Rico 41980 URBAN 0.4449 11640 URBAN 0.4213 -5.30%

Ceiba Municipio, Puerto 

Rico 21940 URBAN 0.3669 41980 URBAN 0.4438 20.96%

Fajardo Municipio, Puerto 21940 URBAN 0.3669 41980 URBAN 0.4438 20.96%
CMS-1627-P 92

Rico

Guanica Municipio, 

Puerto Rico 49500 URBAN 0.3375 38660 URBAN 0.4154 23.08%

Guayanilla Municipio, 

Puerto Rico 49500 URBAN 0.3375 38660 URBAN 0.4154 23.08%

Hatillo Municipio, Puerto 

Rico 41980 URBAN 0.4449 11640 URBAN 0.4213 -5.30%

Luquillo Municipio, 

Puerto Rico 21940 URBAN 0.3669 41980 URBAN 0.4438 20.96%

Penuelas Municipio, 

Puerto Rico 49500 URBAN 0.3375 38660 URBAN 0.4154 23.08%

Quebradillas Municipio, 

Puerto Rico 41980 URBAN 0.4449 11640 URBAN 0.4213 -5.30%

Yauco Municipio, Puerto 

Rico 49500 URBAN 0.3375 38660 URBAN 0.4154 23.08%

Anderson County, South 

Carolina 11340 URBAN 0.8744 24860 URBAN 0.9161 4.77%

Grainger County, 

Tennessee 34100 URBAN 0.6983 28940 URBAN 0.7015 0.46%

Lincoln County, West 

Virginia 16620 URBAN 0.7988 26580 URBAN 0.8846 10.74%

Putnam County, West 

Virginia 16620 URBAN 0.7988 26580 URBAN 0.8846 10.74%

Likewise, IPFs currently located in a rural area may remain rural under the new CBSA 

delineations but experience a change in their rural wage index value due to implementation of 

the new CBSA delineations. Table 18 shows the FY 2015 CBSA delineations and rural 

statewide wage index values, compared with the FY 2016 CBSA delineations and rural statewide 

wage index values, and the percentage change in these values, for those rural areas that would 

change. 

TABLE 18: FY 2016 CHANGES to the STATEWIDE RURAL WAGE INDEX CROSSWALK

County Name

FY 2014 CBSA 

Delineations/ FY 2015 data

FY 2015 CBSA 

Delineations/ FY 2015 data

Change in 

value 

(percent) CBSA Urban/ 

Rural

Wage 

Index

CBS

A

Urban/ 

Rural

Wage 

Index

ALABAMA 1 RURAL 0.6963 1 RURAL 0.6914 -0.70%

ARIZONA 3 RURAL 0.9125 3 RURAL 0.9219 1.03%

CONNECTICUT 7 RURAL 1.1251 7 RURAL 1.1295 0.39%

FLORIDA 10 RURAL 0.8006 10 RURAL 0.8371 4.56%

GEORGIA 11 RURAL 0.7425 11 RURAL 0.7439 0.19%

HAWAII 12 RURAL 1.0741 12 RURAL 1.0872 1.22%
CMS-1627-P 93

ILLINOIS 14 RURAL 0.8362 14 RURAL 0.8369 0.08%

KANSAS 17 RURAL 0.7806 17 RURAL 0.7779 -0.35%

KENTUCKY 18 RURAL 0.7744 18 RURAL 0.7748 0.05%

LOUISIANA 19 RURAL 0.7580 19 RURAL 0.7108 -6.23%

MARYLAND 21 RURAL 0.8554 21 RURAL 0.8746 2.24%

MASSACHUSETTS 22 RURAL 1.3920 22 RURAL 1.1553 -17.00%

MICHIGAN 23 RURAL 0.8207 23 RURAL 0.8288 0.99%

MISSISSIPPI 25 RURAL 0.7589 25 RURAL 0.7570 -0.25%

NEBRASKA 28 RURAL 0.8924 28 RURAL 0.8877 -0.53%

NEW YORK 33 RURAL 0.8208 33 RURAL 0.8192 -0.19%

NORTH CAROLINA 34 RURAL 0.7995 34 RURAL 0.7899 -1.20%

OHIO 36 RURAL 0.8329 36 RURAL 0.8348 0.23%

OREGON 38 RURAL 1.0083 38 RURAL 0.9949 -1.33%

PENNSYLVANIA 39 RURAL 0.8719 39 RURAL 0.8083 -7.29%

SOUTH CAROLINA 42 RURAL 0.8374 42 RURAL 0.8370 -0.05%

TENNESSEE 44 RURAL 0.7365 44 RURAL 0.7277 -1.19%

TEXAS 45 RURAL 0.7855 45 RURAL 0.7847 -0.10%

UTAH 46 RURAL 0.8891 46 RURAL 0.9005 1.28%

VIRGINIA 49 RURAL 0.7674 49 RURAL 0.7554 -1.56%

WASHINGTON 50 RURAL 1.0892 50 RURAL 1.0877 -0.14%

WEST VIRGINIA 51 RURAL 0.7410 51 RURAL 0.7274 -1.84%

WISCONSIN 52 RURAL 0.9041 52 RURAL 0.9087 0.51%

While we believe that the new CBSA delineations would result in wage index values that 

are more representative of the actual costs of labor in a given area, we also recognize that use of 

the new CBSA delineations would result in reduced payments to some IPFs and increased 

payments to other IPFs, due to changes in wage index values. Approximately 23.4 percent of 

IPFs would experience a decrease in wage index values due to CBSA changes, while 12.4

percent of IPFs would experience an increase in wage index values due to CBSA changes. The 

remaining 64.1 percent of IPFs would experience no change in their wage index values (these 

percentages do not sum to 100.0 percent due to rounding). While the wage index CBSA changes 

would be implemented in a budget-neutral fashion, the distributional effects of these CBSA 

changes appear to affect rural IPFs in particular; column 5 in Table 26 in section VII. of this 
CMS-1627-P 94

proposed rule shows that rural providers overall are anticipated to experience payment reductions 

of 0.2 percent, with for-profit rural psychiatric hospitals anticipated to experience the greatest 

reduction of 0.6 percent. We believe that it would be appropriate to provide for a transition 

period to mitigate any negative impacts on facilities that experience reduced payments as a result 

of our adopting the new OMB CBSA delineations. Therefore, we propose to implement these 

CBSA changes using a 1-year transition with a blended wage index for all providers. For FY 

2016, the wage index for each provider would consist of a blend of 50 percent of the FY 2016

IPF wage index using the current OMB delineations and 50 percent of the FY 2016 IPF wage 

index using the new OMB delineations. This results in an average of the 2 values. We propose 

that the FY 2017 IPF PPS wage index and subsequent IPF PPS wage indices would be based 

solely on the new OMB CBSA delineations. We believe a 1-year transition strikes an 

appropriate balance between ensuring that IPF PPS payments are as accurate and stable as

possible while giving IPFs time to adjust to the new CBSA delineations. The proposed FY 2016 

IPF PPS Transitional wage index is located on the CMS website at 

http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/IPFPPS/WageIndex.html.

d. Adjustment for Rural Location and Proposal to Phase Out the Rural Adjustment for IPFs 

Losing Their Rural Adjustment Due to CBSA Changes

In the November 2004 IPF PPS final rule, we provided a 17 percent payment adjustment 

for IPFs located in a rural area. This adjustment was based on the regression analysis, which 

indicated that the per diem cost of rural facilities was 17 percent higher than that of urban 

facilities after accounting for the influence of the other variables included in the regression. For 

FY 2016, we propose to continue to apply a 17 percent payment adjustment for IPFs located in a 

rural area as defined at §412.64(b)(1)(ii)(C). A complete discussion of the adjustment for rural 
CMS-1627-P 95

locations appears in the November 2004 IPF PPS final rule (69 FR 66954). 

As noted in section III.D.1.c. of this proposed rule, we are proposing to adopt OMB 

updates to CBSA delineations. Adoption of the updated CBSAs would change the status of 37 

IPF providers currently designated as “rural” to “urban” for FY 2016 and subsequent fiscal 

years. As such, these 37 newly-urban providers would no longer receive the 17 percent rural 

adjustment. 

While 34 of these 37 rural IPFs that would be designated as urban under the new CBSA 

delineations would experience an increase in their wage index value, all 37 of these IPFs would

lose the 17 percent rural adjustment. Consistent with the transition policy adopted for Inpatient 

Rehabilitation Facilities (IRFs) in FY 2006 (70 FR 47923 through 47927), we considered the 

appropriateness of applying a 3-year phase-out of the rural adjustment for IPFs located in rural

counties that would become urban under the new OMB delineations, given the potentially 

significant payment impacts for these IPFs. We believe that a phase-out of the rural adjustment

transition period for these 37 IPFs specifically is appropriate because we expect these IPFs

would experience a steeper and more abrupt reduction in their payments compared to other IPFs.

Therefore, in addition to the 2-year wage index transition policy noted above, we are 

proposing a budget-neutral 3-year phase-out of the rural adjustment for existing FY 2015 rural 

IPFs that would become urban in FY 2016 and that experience a loss in payments due to changes 

from the new CBSA delineations. Accordingly, the incremental steps needed to reduce the 

impact of the loss of the FY 2015 rural adjustment of 17 percent would be taken over FYs 2016, 

2017 and 2018. This policy would allow rural IPFs that would be classified as urban in FY 2016 

to receive two-thirds of the 2015 rural adjustment for FY 2016, as well as the blended wage 

index. For FY 2017, these IPFs would receive the full FY 2017 wage index and one-third of the 
CMS-1627-P 96

FY 2015 rural adjustment. For FY 2018, these IPFs would receive the full FY 2018 wage index 

without a rural adjustment. We believe a 3-year budget-neutral phase-out of the rural adjustment 

for IPFs that transition from rural to urban status under the new CBSA delineations would best 

accomplish the goals of mitigating the loss of the rural adjustment for existing FY 2015 rural 

IPFs. The purpose of the gradual phase-out of the rural adjustment for these providers is to 

alleviate the significant payment implications for existing rural IPFs that may need time to adjust 

to the loss of their FY 2015 rural payment adjustment or that experience a reduction in payments 

solely because of this re-designation. As stated, this policy is specifically for rural IPFs that 

become urban in FY 2016. We are not implementing a transition policy for urban IPFs that 

become rural in FY 2016 because these IPFs will receive the full rural adjustment of 17 percent 

beginning October 1, 2015.

For the reasons discussed, we are proposing to implement a 3-year budget-neutral phaseout of the rural adjustment for the IPFs that during FY 2015 were designated as rural and for FY 

2016 are designated as urban under the new CBSA system. This is in addition to our proposed 

implementation of a 2-year blended wage index for all IPFs. We believe that the incremental 

reduction of the FY 2015 rural adjustment would be appropriate to mitigate a significant 

reduction in payment. We considered alternative timeframes for phasing out the rural adjustment 

for IPFs which would transition from rural to urban status in FY 2016, but believe that a 3-year 

budget-neutral phase-out of the rural adjustment would appropriately mitigate the adverse 

payment impacts for existing FY 2015 rural IPFs that will be designated as urban IPFs in FY 

2016, while also ensuring that payment rates for these providers are set accurately and 

appropriately. We invite public comment on this proposed policy.

e. Budget neutrality adjustment
CMS-1627-P 97

Changes to the wage index are made in a budget-neutral manner so that updates do not 

increase expenditures. Therefore, for FY 2016, we propose to continue to apply a budgetneutrality adjustment in accordance with our existing budget-neutrality policy. This policy 

requires us to estimate the total amount of IPF PPS payments for FY 2016 using the labor-related 

share and the wage indices from FY 2015 divided by the total estimated IPF PPS payments for 

FY 2016 using the labor-related share and wage indices from FY 2016. The estimated payments 

are based on FY 2014 IPF claims, inflated to the appropriate FY. This quotient is the wage index 

budget-neutrality factor, and it is applied in the update of the Federal per diem base rate for FY 

2016 in addition to the market basket described in section III.A. of this proposed rule. The 

proposed wage index budget-neutrality factor for FY 2016 is 1.0041.

2. Teaching Adjustment 

In the November 2004 IPF PPS final rule, we implemented regulations at 

§412.424(d)(1)(iii) to establish a facility-level adjustment for IPFs that are, or are part of, 

teaching hospitals. The teaching adjustment accounts for the higher indirect operating costs 

experienced by hospitals that participate in graduate medical education (GME) programs. The 

payment adjustments are made based on the ratio of the number of full-time equivalent (FTE) 

interns and residents training in the IPF and the IPF’s average daily census (ADC).

Medicare makes direct GME payments (for direct costs such as resident and teaching 

physician salaries, and other direct teaching costs) to all teaching hospitals including those paid 

under a PPS, and those paid under the TEFRA rate-of-increase limits. These direct GME 

payments are made separately from payments for hospital operating costs and are not part of the 

IPF PPS. The direct GME payments do not address the estimated higher indirect operating costs

teaching hospitals may face. 
CMS-1627-P 98

The results of the regression analysis of FY 2002 IPF data established the basis for the 

payment adjustments included in the November 2004 IPF PPS final rule. The results showed 

that the indirect teaching cost variable is significant in explaining the higher costs of IPFs that 

have teaching programs. We calculated the teaching adjustment based on the IPF's "teaching 

variable," which is one plus the ratio of the number of FTE residents training in the IPF (subject 

to limitations described below) to the IPF's ADC. 

We established the teaching adjustment in a manner that limited the incentives for IPFs to 

add FTE residents for the purpose of increasing their teaching adjustment. We imposed a cap on 

the number of FTE residents that may be counted for purposes of calculating the teaching 

adjustment. The cap limits the number of FTE residents that teaching IPFs may count for the 

purpose of calculating the IPF PPS teaching adjustment, not the number of residents teaching 

institutions can hire or train. We calculated the number of FTE residents that trained in the IPF 

during a "base year" and used that FTE resident number as the cap. An IPF's FTE resident cap is 

ultimately determined based on the final settlement of the IPF's most recent cost report filed 

before November 15, 2004 (that is, the publication date of the IPF PPS final rule). A complete 

discussion on the temporary adjustment to the FTE cap to reflect residents added due to hospital 

closure and by residency program appears in the January 27, 2011 IPF PPS proposed rule (76 FR 

5018 through 5020) and the May 6, 2011 IPF PPS final rule (76 R 26453 through 26456).

In the regression analysis, the logarithm of the teaching variable had a coefficient value 

of 0.5150. We converted this cost effect to a teaching payment adjustment by treating the 

regression coefficient as an exponent and raising the teaching variable to a power equal to the 

coefficient value. We note that the coefficient value of 0.5150 was based on the regression 

analysis holding all other components of the payment system constant. A complete discussion of 
CMS-1627-P 99

how the teaching adjustment was calculated appears in the November 2004 IPF PPS final rule 

(69 FR 66954 through 66957) and the May 2008 IPF PPS notice (73 FR 25721). As with other 

adjustment factors derived through the regression analysis, we do not plan to rerun the teaching 

adjustment factors in the regression analysis until we more fully analyze IPF PPS data. 

Therefore, in this proposed rule, for FY 2016, we propose to continue to retain the coefficient 

value of 0.5150 for the teaching adjustment to the Federal per diem base rate. 

3. Cost of Living Adjustment for IPFs Located in Alaska and Hawaii. 

The IPF PPS includes a payment adjustment for IPFs located in Alaska and Hawaii based 

upon the county in which the IPF is located. As we explained in the November 2004 IPF PPS 

final rule, the FY 2002 data demonstrated that IPFs in Alaska and Hawaii had per diem costs that 

were disproportionately higher than other IPFs. Other Medicare PPSs (for example, the IPPS 

and LTCH PPS) adopted a cost of living adjustment (COLA) to account for the cost differential 

of care furnished in Alaska and Hawaii. 

We analyzed the effect of applying a COLA to payments for IPFs located in Alaska and 

Hawaii. The results of our analysis demonstrated that a COLA for IPFs located in Alaska and 

Hawaii would improve payment equity for these facilities. As a result of this analysis, we 

provided a COLA in the November 2004 IPF PPS final rule. 

A COLA for IPFs located in Alaska and Hawaii is made by multiplying the nonlaborrelated portion of the Federal per diem base rate by the applicable COLA factor based on the 

COLA area in which the IPF is located. 

The COLA factors are published on the Office of Personnel Management (OPM) website 

(http://www.opm.gov/oca/cola/rates.asp). 

We note that the COLA areas for Alaska are not defined by county as are the COLA 
CMS-1627-P 100

areas for Hawaii. In 5 CFR 591.207, the OPM established the following COLA areas:

 City of Anchorage, and 80-kilometer (50-mile) radius by road, as measured from the

Federal courthouse;

 City of Fairbanks, and 80-kilometer (50-mile) radius by road, as measured from the 

Federal courthouse;

 City of Juneau, and 80-kilometer (50-mile) radius by road, as measured from the 

Federal courthouse;

 Rest of the State of Alaska.

As stated in the November 2004 IPF PPS final rule, we update the COLA factors 

according to updates established by the OPM. However, sections 1911 through 1919 of the 

Nonforeign Area Retirement Equity Assurance Act, as contained in subtitle B of title XIX of the 

National Defense Authorization Act (NDAA) for Fiscal Year 2010 (Pub. L. 111-84, October 28, 

2009), transitions the Alaska and Hawaii COLAs to locality pay. Under section 1914 of Pub. L. 

111-84, locality pay is being phased in over a 3-year period beginning in January 2010, with 

COLA rates frozen as of the date of enactment, October 28, 2009, and then proportionately 

reduced to reflect the phase-in of locality pay. 

When we published the proposed COLA factors in the January 2011 IPF PPS proposed 

rule (76 FR 4998), we inadvertently selected the FY 2010 COLA rates which had been reduced

to account for the phase-in of locality pay. We did not intend to propose the reduced COLA 

rates because that would have understated the adjustment. Since the 2009 COLA rates did not 

reflect the phase-in of locality pay, we finalized the FY 2009 COLA rates for RY 2010 through 

RY 2014. 

In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), CMS established a 
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methodology for FY 2014 to update the COLA factors for Alaska and Hawaii. Under that 

methodology, we use a comparison of the growth in the Consumer Price Indices (CPIs) in 

Anchorage, Alaska and Honolulu, Hawaii relative to the growth in the overall CPI as published 

by the Bureau of Labor Statistics (BLS) to update the COLA factors for all areas in Alaska and 

Hawaii, respectively. As discussed in the FY 2013 IPPS/LTCH proposed rule (77 FR 28145), 

because BLS publishes CPI data for only Anchorage, Alaska and Honolulu, Hawaii, our 

methodology for updating the COLA factors uses a comparison of the growth in the CPIs for 

those cities relative to the growth in the overall CPI to update the COLA factors for all areas in 

Alaska and Hawaii, respectively. We believe that the relative price differences between these 

cities and the United States (as measured by the CPIs mentioned above) are generally appropriate 

proxies for the relative price differences between the “other areas” of Alaska and Hawaii and the 

United States.

The CPIs for “All Items” that BLS publishes for Anchorage, Alaska, Honolulu, Hawaii, 

and for the average U.S. city are based on a different mix of commodities and services than is 

reflected in the nonlabor-related share of the IPPS market basket. As such, under the 

methodology we established to update the COLA factors, we calculated a “reweighted CPI” 

using the CPI for commodities and the CPI for services for each of the geographic areas to 

mirror the composition of the IPPS market basket nonlabor-related share. The current 

composition of BLS’ CPI for “All Items” for all of the respective areas is approximately 40 

percent commodities and 60 percent services. However, the nonlabor-related share of the IPPS 

market basket is comprised of 60 percent commodities and 40 percent services. Therefore, under 

the methodology established for FY 2014 in the FY 2013 IPPS/LTCH PPS final rule, we created 

reweighted indexes for Anchorage, Alaska, Honolulu, Hawaii, and the average U.S. city using 
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the respective CPI commodities index and CPI services index and applying the approximate 

60/40 weights from the IPPS market basket. This approach is appropriate because we would 

continue to make a COLA for hospitals located in Alaska and Hawaii by multiplying the 

nonlabor-related portion of the standardized amount by a COLA factor.

Under the COLA factor update methodology established in the FY 2014 IPPS/LTCH 

final rule, we adjust payments made to hospitals located in Alaska and Hawaii by incorporating a 

25-percent cap on the CPI-updated COLA factors. We note that OPM’s COLA factors were 

calculated with a statutorily mandated cap of 25 percent, and since at least 1984, we have 

exercised our discretionary authority to adjust Alaska and Hawaii payments by incorporating this 

cap. In keeping with this historical policy, we would continue to use such a cap, as our proposal 

is based on OPM’s COLA factors. We believe this approach is appropriate because our CPIupdated COLA factors use the 2009 OPM COLA factors as a basis. 

In FY 2015 IPF PPS rulemaking, we adopted the same methodology for the COLA 

factors applied under the IPPS because IPFs are hospitals with a similar mix of commodities and 

services. We think it is appropriate to have a consistent policy approach with that of other 

hospitals in Alaska and Hawaii. Therefore, in the FY 2015 IPF PPS final rule, we adopted the 

cost of living adjustment factors shown in the Addendum for IPFs located in Alaska and Hawaii. 

Under IPPS COLA policy, the COLA updates are determined every four years, when the IPPS 

market basket is rebased. Since the IPPS COLA factors were last updated in FY 2014, they are 

not scheduled to be updated again until FY 2018. As such, we propose to continue using the 

existing IPF PPS COLA factors in effect in FY 2015 for FY 2016. The IPF PPS COLA factors 

for FY 2016 are shown in the Addendum of this proposed rule.

4. Proposed Adjustment for IPFs with a Qualifying Emergency Department (ED)
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The IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. We 

provide an adjustment to the Federal per diem base rate to account for the costs associated with 

maintaining a full-service ED. The adjustment is intended to account for ED costs incurred by a 

freestanding psychiatric hospital with a qualifying ED or a distinct part psychiatric unit of an 

acute care hospital or a CAH, for preadmission services otherwise payable under the Medicare 

Outpatient Prospective Payment System (OPPS), furnished to a beneficiary on the date of the 

beneficiary’s admission to the hospital and during the day immediately preceding the date of 

admission to the IPF (see §413.40(c)(2)), and the overhead cost of maintaining the ED. This 

payment is a facility-level adjustment that applies to all IPF admissions (with one exception 

described below), regardless of whether a particular patient receives preadmission services in the 

hospital's ED.

The ED adjustment is incorporated into the variable per diem adjustment for the first day 

of each stay for IPFs with a qualifying ED. That is, IPFs with a qualifying ED receive an 

adjustment factor of 1.31 as the variable per diem adjustment for day 1 of each stay. If an IPF 

does not have a qualifying ED, it receives an adjustment factor of 1.19 as the variable per diem 

adjustment for day 1 of each patient stay. 

The ED adjustment is made on every qualifying claim except as described below. As 

specified in §412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is discharged 

from an acute care hospital or CAH and admitted to the same hospital's or CAH's psychiatric 

unit. We clarified in the November 2004 IPF PPS final rule (69 FR 66960) that an ED 

adjustment is not made in this case because the costs associated with ED services are reflected in 

the DRG payment to the acute care hospital or through the reasonable cost payment made to the 

CAH. 
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Therefore, when patients are discharged from an acute care hospital or CAH and admitted 

to the same hospital or CAH's psychiatric unit, the IPF receives the 1.19 adjustment factor as the 

variable per diem adjustment for the first day of the patient's stay in the IPF. 

For FY 2016, we are proposing to continue to retain the 1.31 adjustment factor for IPFs 

with qualifying EDs. A complete discussion of the steps involved in the calculation of the ED 

adjustment factor appears in the November 2004 IPF PPS final rule (69 FR 66959 through 

66960) and the May 2006 IPF PPS final rule (71 FR 27070 through 27072).

E. Other Proposed Payment Adjustments and Policies 

1. Outlier Payment Overview

The IPF PPS includes an outlier adjustment to promote access to IPF care for those 

patients who require expensive care and to limit the financial risk of IPFs treating unusually 

costly patients. In the November 2004 IPF PPS final rule, we implemented regulations at 

§412.424(d)(3)(i) to provide a per-case payment for IPF stays that are extraordinarily costly. 

Providing additional payments to IPFs for extremely costly cases strongly improves the accuracy 

of the IPF PPS in determining resource costs at the patient and facility level. These additional 

payments reduce the financial losses that would otherwise be incurred in treating patients who 

require more costly care and, therefore, reduce the incentives for IPFs to under-serve these 

patients. 

We make outlier payments for discharges in which an IPF's estimated total cost for a case 

exceeds a fixed dollar loss threshold amount (multiplied by the IPF's facility-level adjustments) 

plus the Federal per diem payment amount for the case.

In instances when the case qualifies for an outlier payment, we pay 80 percent of the 

difference between the estimated cost for the case and the adjusted threshold amount for days 1 
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through 9 of the stay (consistent with the median LOS for IPFs in FY 2002), and 60 percent of 

the difference for day 10 and thereafter. We established the 80 percent and 60 percent loss 

sharing ratios because we were concerned that a single ratio established at 80 percent (like other 

Medicare PPSs) might provide an incentive under the IPF per diem payment system to increase 

LOS in order to receive additional payments. 

After establishing the loss sharing ratios, we determined the current FY 2015 fixed dollar 

loss threshold amount through payment simulations designed to compute a dollar loss beyond 

which payments are estimated to meet the 2 percent outlier spending target. Each year when we 

update the IPF PPS, we simulate payments using the latest available data to compute the fixed 

dollar loss threshold so that outlier payments represent 2 percent of total projected IPF PPS 

payments. 

2. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount 

In accordance with the update methodology described in §412.428(d), we propose to 

update the fixed dollar loss threshold amount used under the IPF PPS outlier policy. Based on 

the regression analysis and payment simulations used to develop the IPF PPS, we established a 2 

percent outlier policy which strikes an appropriate balance between protecting IPFs from 

extraordinarily costly cases while ensuring the adequacy of the Federal per diem base rate for all 

other cases that are not outlier cases. 

Based on an analysis of the latest available data (that is, FY 2014 IPF claims) and rate 

increases, we believe it is necessary to update the fixed dollar loss threshold amount in order to 

maintain an outlier percentage that equals 2 percent of total estimated IPF PPS payments. To 

update the IPF outlier threshold amount for FY 2016, we propose to use FY 2014 claims data 

and the same methodology that we used to set the initial outlier threshold amount in the May 
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2006 IPF PPS final rule (71 FR 27072 and 27073), which is also the same methodology that we 

used to update the outlier threshold amounts for years 2008 through 2015. Based on an analysis 

of this updated data, we estimate that IPF outlier payments as a percentage of total estimated 

payments are approximately 2.3 percent in FY 2015. Therefore, we propose to update the outlier 

threshold amount to $9,825 to maintain estimated outlier payments at approximately 2 percent of 

total estimated aggregate IPF payments for FY 2016.

3. Proposed Update to IPF Cost-to-Charge Ratio Ceilings

Under the IPF PPS, an outlier payment is made if an IPF's cost for a stay exceeds a fixed 

dollar loss threshold amount plus the IPF PPS amount. In order to establish an IPF's cost for a 

particular case, we multiply the IPF's reported charges on the discharge bill by its overall cost-tocharge ratio (CCR). This approach to determining an IPF's cost is consistent with the approach 

used under the IPPS and other PPSs. In the June 2003 IPPS final rule (68 FR 34494), we 

implemented changes to the IPPS policy used to determine CCRs for acute care hospitals 

because we became aware that payment vulnerabilities resulted in inappropriate outlier 

payments. Under the IPPS, we established a statistical measure of accuracy for CCRs in order to 

ensure that aberrant CCR data did not result in inappropriate outlier payments. 

As we indicated in the November 2004 IPF PPS final rule (69 FR 66961), because we 

believe that the IPF outlier policy is susceptible to the same payment vulnerabilities as the IPPS, 

we adopted a method to ensure the statistical accuracy of CCRs under the IPF PPS. Specifically, 

we adopted the following procedure in the November 2004 IPF PPS final rule: We calculated 2

national ceilings, one for IPFs located in rural areas and one for IPFs located in urban areas. We 

computed the ceilings by first calculating the national average and the standard deviation of the 

CCR for both urban and rural IPFs using the most recent CCRs entered in the CY 2015 Provider 
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Specific File. 

To determine the rural and urban ceilings, we multiplied each of the standard deviations 

by 3 and added the result to the appropriate national CCR average (either rural or urban). The 

upper threshold CCR for IPFs in FY 2016 is 1.9041 for rural IPFs, and 1.6881 for urban IPFs, 

based on CBSA-based geographic designations. If an IPF's CCR is above the applicable ceiling, 

the ratio is considered statistically inaccurate, and we assign the appropriate national (either rural 

or urban) median CCR to the IPF. 

We apply the national CCRs to the following situations: 

 New IPFs that have not yet submitted their first Medicare cost report. We continue to use 

these national CCRs until the facility’s actual CCR can be computed using the first tentatively or 

final settled cost report.

 IPFs whose overall CCR is in excess of 3 standard deviations above the corresponding 

national geometric mean (that is, above the ceiling).

 Other IPFs for which the MAC obtains inaccurate or incomplete data with which to 

calculate a CCR. 

We are not proposing to make any changes to the application of the national CCRs or to 

the procedures for updating the CCR ceilings in FY 2016. However, we are proposing to update

the FY 2016 national median and ceiling CCRs for urban and rural IPFs based on the CCRs 

entered in the latest available IPF PPS Provider Specific File. Specifically, for FY 2016, and to 

be used in each of the 3 situations listed above, using the most recent CCRs entered in the CY 

2015 Provider Specific File we estimate the national median CCR of 0.6210 for rural IPFs and 

the national median CCR of 0.4675 for urban IPFs. These calculations are based on the IPF's 

location (either urban or rural) using the CBSA-based geographic designations.
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A complete discussion regarding the national median CCRs appears in the November 

2004 IPF PPS final rule (69 FR 66961 through 66964).

IV. Other Payment Policy Issues

A. ICD-10-CM and ICD-10-PCS Implementation

We remind IPF providers that CMS is implementing the International Classification of 

Diseases, 10th Revision, Clinical Modification (ICD–10–CM) as the HIPAA designated code set 

for reporting diseases, injuries, impairments, other health related problems, their manifestations, 

and causes of injury as of October 1, 2015. Below is a brief history of key activities leading to 

the October 1, 2015 implementation date.

In the Standards for Electronic Transactions final rule, published in the Federal Register 

on August 17, 2000 (65 FR 50312), the Department adopted the International Classification of 

Diseases, 9th Revision, Clinical Modification (ICD–9–CM) as the HIPAA designated code set 

for reporting diseases, injuries, impairments, other health related problems, their manifestations, 

and causes of injury. Therefore, on January 1, 2005 when the IPF PPS began, we used ICD–9–

CM as the designated code set for the IPF PPS. IPF claims with a principal diagnosis included in 

Chapter Five of the ICD–9–CM are paid the Federal per diem base rate and all other applicable 

adjustments, including any applicable DRG adjustment. 

Together with the rest of the healthcare industry, CMS was scheduled to implement the 

10th revision of the ICD coding scheme, that is, ICD–10–CM, on October 1, 2014. Hence, in the 

FY 2014 IPF PPS final rule (78 FR 46741-46742), we finalized a policy that ICD–10–CM codes 

will be used in IPF PPS. 

On April 1, 2014, the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. No. 

113-93) was enacted. Section 212 of PAMA, titled “Delay in Transition from ICD-9 to ICD-10 
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Code Sets,” provided that “[t]he Secretary of Health and Human Services may not, prior to 

October 1, 2015, adopt ICD-10 code sets as the standard for code sets under section 1173(c) of 

the Social Security Act (42 U.S.C. 1320d-2(c)) and section 162.1002 of title 45, Code of Federal 

Regulations.” On May 1, 2014, the Secretary announced that HHS expected to issue an interim 

final rule that would require use of ICD–10–CM beginning October 1, 2015 and would continue 

to require use of ICD–9–CM through September 30, 2015. This announcement is available on 

the CMS web site at http://cms.gov/Medicare/Coding/ICD10/index.html. HHS finalized the new 

compliance date of October 1, 2015 for ICD–10–CM and ICD–10–PCS in an August 4, 2014 

final rule titled ‘‘Administrative Simplification: Change to the Compliance Date for the 

International Classification of Diseases, 10th Revision (ICD–10–CM and ICD–10–PCS)’’ (79 

FR 45128). This rule also requires HIPAA covered entities to continue to use the ICD–9-CM 

code set through September 30, 2015. Therefore, beginning October 1, 2015, we require use of 

the ICD-10-CM and ICD-10-PCS codes for reporting the MS-DRG and comorbidity adjustment 

factors for IPF services. 

Every year, changes to the ICD-10-CM and the ICD-10-PCS coding system will be 

addressed in the IPPS proposed and final rules. The changes to the codes are effective October 1 

of each year and must be used by acute care hospitals as well as other providers to report 

diagnostic and procedure information. The IPF PPS has always incorporated ICD–9–CM coding 

changes made in the annual IPPS update and will continue to do so for the ICD-10-CM and ICD10-PCS coding changes. We will continue to publish coding changes in a Transmittal/Change 

Request, similar to how coding changes are announced by the IPPS and LTCH PPS. The coding 

changes relevant to the IPF PPS are also published in the IPF PPS proposed and final rules, or in 

IPF PPS update notices. In §412.428(e), we indicate that CMS will publish information 
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pertaining to the annual update for the IPF PPS, which includes describing the ICD-9-CM coding 

changes and DRG classification changes discussed in the annual update to the hospital IPPS 

regulations. Because ICD-10-CM will be implemented on October 1, 2015, we need to update 

the regulation language at §412.428(e) to refer to ICD-10-CM, rather than ICD-9-CM. 

Therefore, we propose to revise §412.428(e) to state that the information we will publish 

annually in the Federal Register to describe IPF PPS updates would describe the ICD-10-CM 

coding changes and DRG classification changes discussed in the annual update to the hospital 

inpatient prospective payment system regulations. In the FY 2015 IPF PPS final rule (79 FR 

45945 through 46946), the MS-DRGs were converted so that the MS-DRG assignment logic 

uses ICD-10-CM/PCS codes directly. When an IPF submits a claim for discharges, the ICD-10-

CM/PCS diagnosis and procedure codes will be assigned to the correct MS-DRG. In the FY 

2015 IPF PPS final rule, we also identified the ICD-10-CM/PCS codes that are eligible for 

comorbidity payment adjustments under the IPF PPS (79 FR 45947 through 45955). 

The ICD-10-CM guidelines are updated each year along with the ICD-10-CM code 

set. To find the annual coding guidelines, go to CDC’s website at 

http://www.cdc.gov/nchs/icd/icd10cm.htm or the annual ICD-10-CM updates posted on the CMS 

ICD-10 website at http://www.cms.gov/Medicare/Coding/ICD10/index.html.

B. Status of Future Refinements

For RY 2012, we identified several areas of concern for future refinement, and we invited 

comments on these issues in our RY 2012 proposed and final rules. For further discussion of 

these issues and to review the public comments, we refer readers to the RY 2012 IPF PPS 

proposed rule (76 FR 4998) and final rule (76 FR 26432). 

We have delayed making refinements to the IPF PPS until we have completed a thorough 
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analysis of IPF PPS data on which to base those refinements. Specifically, we will delay

updating the adjustment factors derived from the regression analysis until we have IPF PPS data 

that include as much information as possible regarding the patient-level characteristics of the 

population that each IPF serves. We have begun the necessary analysis to better understand IPF 

industry practices so that we may refine the IPF PPS in the future, as appropriate. 

IPF Covered Services

The IPF PPS established the Federal per diem base rate for each patient day in an IPF 

from the national average routine operating, ancillary, and capital costs. Preliminary analysis 

reveals that in 2012 to 2013, over 20 percent of IPF stays show no reported ancillary costs, such 

as laboratory and drug costs, in cost reports or charges on claims. The majority of these stays

with zero ancillary costs or charges were in for-profit, free-standing IPF hospitals. We would 

expect that patients admitted to an IPF would undergo laboratory testing as part of the admission 

history and physical. We would also expect that most patients requiring hospitalization for 

active psychiatric treatment would need drugs. Therefore, we were surprised when the analysis 

showed such a large number of stays reporting no laboratory services and no drugs were 

provided throughout the hospitalization. Until further analysis is completed, we can only 

surmise that the stays did not require ancillaries and therefore, were not provided, or that the 

ancillary services were separately billed. 

We remind the industry that CMS pays only the inpatient psychiatric facility for services 

furnished to a Medicare beneficiary who is an inpatient of that inpatient psychiatric facility, 

except for certain professional services, and that payments made under this subpart are payments 

in full for all inpatient hospital services, provided directly or under arrangement (see 42 CFR 

412.404(d)), as specified in 42 CFR 409.10. 
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The covered services specified in §409.10(a), which apply to IPFs, include the following:

bed and board; nursing services and other related services; use of hospital or CAH facilities; 

medical social services; drugs, biologicals, supplies, appliances, and equipment; certain other 

diagnostic or therapeutic services; medical or surgical services provided by certain interns or 

residents-in-training; and transportation services, including transport by ambulance.

Only the professional services listed in §409.10(b) can be separately billed for a Medicare 

beneficiary who is an inpatient at an IPF, including services of physicians, physician assistants, 

nurse practitioners, clinical nurse specialists, certified nurse mid-wives, anesthetists, and 

qualified psychologists. (see §409.10(b) for specifics on how these professions and services are 

defined. These regulations are available online at the electronic Code of Federal Regulations, at 

http://www.ecfr.gov/cgi-bin/text-idx?c=ecfr&tpl=%2Findex.tpl.)

Ancillary costs such as laboratory costs and drugs are already included in the Medicare 

IPF PPS per diem payment and should not be unbundled and billed separately to Medicare. We 

expect that the IPF would be recording the cost of all drugs provided to its Medicare patients on 

its Medicare cost reports, and reporting charges for those drugs on its Medicare claims. We 

expect that when an IPF contracts with an outside laboratory to provide services to its Medicare 

inpatients, the IPF would instruct the laboratory to bill the IPF and not to bill Medicare.

Similarly, drugs provided to IPF Medicare inpatients where Medicare is the primary payer 

should not be billed to Part D or to other insurers. 

We are continuing to analyze claims and cost report data that do not include ancillary 

charges or costs, and will be sharing our findings with the Center for Program Integrity and the 

Office of Financial Management for further investigation, as the results warrant. Our refinement 

analysis is dependent on recent precise data for costs, including ancillary costs. We will 
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continue to collect these data until an accurate refinement analysis can be performed. Therefore, 

we are not proposing refinements in this proposed rule. Once we have gathered timely and 

accurate data, we will analyze that data with the expectation of a refinement update in 

future rulemaking. We invite comments on this issue of zero ancillary costs to better understand 

industry practices. 

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

1. Statutory Authority

Section 1886(s)(4) of the Act, as added and amended by sections 3401(f) and 10322(a) of 

the Affordable Care Act, requires the Secretary to implement a quality reporting program for 

inpatient psychiatric hospitals and psychiatric units. Section 1886(s)(4)(A)(i) of the Act requires 

that, for FY 20142and each subsequent fiscal year, the Secretary must reduce any annual update 

to a standard Federal rate for discharges occurring during the rate year by 2.0 percentage points 

for any inpatient psychiatric hospital or psychiatric unit that does not comply with quality data 

submission requirements with respect to an applicable fiscal year.

As provided in section 1886(s)(4)(A)(ii) of the Act, the application of the reduction for 

failure to report under section 1886(s)(4)(A)(i) of the Act may result in an annual update of less 

 

2 The statute uses the term “rate year” (RY). However, beginning with the annual update of the inpatient psychiatric 

facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS 

update with the annual update of the ICD-9-CM codes, effective on October 1 of each year. This change allowed 

for annual payment updates and the ICD-9-CM coding update to occur on the same schedule and appear in the same 

Federal Register document, promoting administrative efficiency. To reflect the change to the annual payment rate 

update cycle, we revised the regulations at 42 CFR 412.402 to specify that, beginning October 1, 2012, the RY 

update period would be the 12-month period from October 1 through September 30, which we refer to as a “fiscal 

year” (FY) (76 FR 26435). Therefore, with respect to the IPFQR Program, the terms “rate year”, as used in the 

statute, and “fiscal year” as used in the regulation, both refer to the period from October 1 through September 30. 

For more information regarding this terminology change, we refer readers to section III. of the RY 2012 IPF PPS 

final rule (76 FR 26434 through 26435). 
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than 0.0 percent for a fiscal year, and may result in payment rates under section 1886(s)(1) of the 

Act being less than the payment rates for the preceding year. In addition, section 1886(s)(4)(B) 

of the Act requires that the application of the reduction to a standard Federal rate update be 

noncumulative across fiscal years. Thus, any reduction applied under section 1886(s)(4)(A) of 

the Act will apply only with respect to the fiscal year rate involved and the Secretary may not 

take into account the reduction in computing the payment amount under the system described in 

section 1886(s)(1) of the Act for subsequent years.

Section 1886(s)(4)(C) of the Act requires that, for FY 2014 (October 1, 2013, through 

September 30, 2014) and each subsequent year, each psychiatric hospital and psychiatric unit 

must submit to the Secretary data on quality measures as specified by the Secretary. The data 

must be submitted in a form and manner and at a time specified by the Secretary. Under section 

1886(s)(4)(D)(i) of the Act, measures selected for the quality reporting program must have been 

endorsed by the entity with a contract under section 1890(a) of the Act. The National Quality 

Forum (NQF) currently holds this contract.

Section 1886(s)(4)(D)(ii) of the Act provides that, in the case of a specified area or 

medical topic determined appropriate by the Secretary for which a feasible and practical measure 

has not been endorsed by the entity with a contract under section 1890(a) of the Act, the 

Secretary may specify a measure that is not so endorsed as long as due consideration is given to 

measures that have been endorsed or adopted by a consensus organization identified by the 

Secretary. Pursuant to section 1886(s)(4)(D)(iii) of the Act, the Secretary must publish the 

measures applicable to the FY 2014 IPFQR Program no later than October 1, 2012.

Section 1886(s)(4)(E) of the Act requires the Secretary to establish procedures for 

making public the data submitted by inpatient psychiatric hospitals and psychiatric units under 
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the IPFQR Program. These procedures must ensure that a facility has the opportunity to review 

its data prior to the data being made public. The Secretary must report quality measures that 

relate to services furnished by the psychiatric hospitals and units on the CMS website.

2. Covered Entities

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we established that the IPFQR 

Program’s quality reporting requirements cover those psychiatric hospitals and psychiatric units 

paid under Medicare’s IPF PPS (42 CFR 412.404(b)). Generally, psychiatric hospitals and 

psychiatric units within acute care and critical access hospitals that treat Medicare patients are 

paid under the IPF PPS. Consistent with prior rules, we continue to use the term “inpatient 

psychiatric facility” (IPF) to refer to both inpatient psychiatric hospitals and psychiatric units. 

This usage follows the terminology in our IPF PPS regulations at §412.402. For more 

information on covered entities, we refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 

FR 53645). 

3. Considerations in Selecting Quality Measures

Our objective in selecting quality measures is to balance the need for information on the 

full spectrum of care delivery and the need to minimize the burden of data collection and 

reporting. We have focused on measures that evaluate critical processes of care that have 

significant impact on patient outcomes and support CMS and HHS priorities for improved 

quality and efficiency of care provided by IPFs. We refer readers to the FY 2013 IPPS/LTCH 

PPS final rule Section 4.a. (77 FR 53645 through 53646) for a detailed discussion of the 

considerations taken into account in selecting quality measures. 

Before being proposed for inclusion in the IPFQR Program, measures are placed on a list 

of measures under consideration, which is published annually by December 1 on behalf of CMS 
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by the NQF. In compliance with section 1890A(a)(2) of the Act, measures proposed for the 

IPFQR Program were included in 2 publicly available documents: “List of Measures under 

Consideration for December 1, 2013,” and “List of Measures under Consideration for 

December 1, 2014” 

(http://www.qualityforum.org/Setting_Priorities/Partnership/Measure_Applications_Partnership.

aspx). The Measure Applications Partnership (MAP), a multi-stakeholder group convened by 

the NQF, reviews the measures under consideration for the IPFQR Program, among other 

Federal programs, and provides input on those measures to the Secretary. The MAP’s 2014 and 

2015 recommendations for quality measures under consideration are captured in the following 

documents: “MAP Pre-Rulemaking Report: 2014 Recommendations on Measures for More than 

20 Federal Programs” (http://www.qualityforum.org/Publications/2014/01/MAP_PreRulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Prog

rams.aspx) and “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” 

(http://www.qualityforum.org/Publications/2015/01/Process_and_Approach_for_MAP_PreRulemaking_Deliberations_2015.aspx). We considered the input and recommendations 

provided by the MAP in selecting all measures for the Program, including those discussed below. 

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

Since the inception of the IPFQR Program in FY 2013, we have adopted a total of 14 

mandatory measures. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 53652), 

we adopted six chart-abstracted IPF quality measures for the FY 2014 payment determination 

and subsequent years. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through 50895), 

we added 2 measures for the FY 2016 payment determination and subsequent years. In the FY 

2015 IPF PPS final rule (79 FR 45963 through 45974), we finalized the addition of 2 new 
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measures to the IPFQR Program to those already adopted for the FY 2016 payment 

determination and subsequent years, and finalized four quality measures for the FY 2017 

payment determination and subsequent years.

C. Proposed Removal of HBIPS-4 from the IPFQR Program Measure Set for the FY 2017 

Payment Determination and Subsequent Years

We first adopted HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications in 

the FY 2013 IPPS/LTCH PPS final rule (77 FR 53649 through 53650). We refer readers to that 

rule for a detailed discussion of the measure. At the time that we adopted the measure, it was 

NQF-endorsed and intended for use in conjunction with HBIPS-5 Patients Discharged on 

Multiple Antipsychotic Medications with Appropriate Justification. However, NQF removed its 

endorsement of HBIPS-4 in January 2014. The NQF’s Behavioral Health Steering Committee, 

in its May 2014 Technical Expert Panel Report, found that current evidence indicated that 

HBIPS-4 “does not allow for the distinction of differences in providers . . . .”3 Moreover, the 

Steering Committee noted that HBIPS-4 “is not a measure of quality of patient care . . . and there 

is insufficient evidence to warrant the endorsement of this measure given the use of HBIPS-5, 

which addresses patients discharged on multiple antipsychotic medications with appropriate 

justification.”4 For these reasons, the Steering Committee did not re-endorse HBIPS-4. 

As we stated in the FY 2013 IPPS/LTCH PPS final rule, we originally proposed HBIPS4, in part, because HBIPS-4 and HBIPS-5 were intended to be reported as a set (77 FR 53649). 

However, as discussed above, NQF no longer believes HBIPS-4 is necessary in that set, and we 

 

3 Behavioral Health Endorsement Maintenance 2014, Phase 2, Technical Report, 67, (May 9, 2014). Available at 

http://www.qualityforum.org/Publications/2014/05/Behavioral_Health_Endorsement_Maintenance_2014_-

_Phase_II.aspx.

4

Ibid.
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agree. We have the authority to maintain measures that are not NQF-endorsed under section 

1886(s)(4)(D)(ii) of the Act. However, based on the loss of NQF endorsement and because 

providers must still submit data for HBIPS-5, which we believe sufficiently includes the 

information HBIPS-4 was intended to collect, we believe removal of HBIPS-4 from the IPFQR 

Program is warranted. We note that the data collection period for FY 2016 has ended and 

providers are required to submit this data before this rule will be finalized. Therefore, FY 2017 

is the first year that we would be able to remove this measure from the program. 

In summary, Table 19, below, identifies the measure that we are proposing to remove 

beginning with the FY 2017 payment determination. We request comment on this proposal.

Table 19- IPFQR Program Measure Proposed to be Removed for the FY 2017 Payment 

Determination and Subsequent Years 

NQF #

Measure ID Measure

N/A HBIPS-4

Patients Discharged on Multiple 

Antipsychotic Medications

D. New Quality Measures Proposed for the FY 2018 Payment Determination and Subsequent 

Years

For the FY 2018 payment determination and subsequent years, we are proposing five new 

measures. The sections below outline our rationale for proposing these measures. 

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the subset measure 

TOB-3a Tobacco Use Treatment at Discharge (NQF #1656)

Tobacco use is one of the greatest contributors of morbidity and mortality in the United 

States, accounting for more than 435,000 deaths annually.5 Smoking is a known cause of 

 

5 Centers for Disease Control and Prevention. Annual Smoking-Attributable Mortality, Years of Potential Life Lost, 

and Productivity Losses—United States, 2000-2004." Morb Mortal Wkly Rep. 2008. 57(45): 1226-1228. Available 

at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5745a3.htm.
CMS-1627-P 119

multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive 

pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases.6 

This health issue has significant implications for persons with mental illness and substance use 

disorders. Tobacco use is much higher among people with co-existing mental health conditions 

than for the general population.7 One study has estimated that these individuals are twice as 

likely to smoke as the rest of the population.8 Tobacco use also creates a heavy financial cost to 

both individuals and society. Smoking-attributable health care expenditures are estimated at $96 

billion per year in direct medical expenses and $97 billion in lost productivity.9 

Strong and consistent evidence demonstrates that timely tobacco dependence 

interventions for patients using tobacco can significantly reduce the risk of developing a tobaccorelated disease, as well as provide improved health outcomes for those already suffering from a 

tobacco-related disease.10 Even a minimal intervention has been shown to result in cessation.11 

Research discloses that tobacco users hospitalized with psychiatric illnesses who enter into 

 

6 U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon 

General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 

2004.

7 Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission’s New Tobacco Cessation 

Measures – Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174. Available at 

http://www.nejm.org/doi/full/10.1056/nejmp1115176. 

8 Lasser K, Boyd JW, Woolhandler S, Himmelstein, DU, McCormick D, Bor DH. Smoking and mental illness: A 

population-based prevalence study. JAMA. 2000;284(20):2606-2610.

9 Centers for Disease Control and Prevention. “Best Practices for Comprehensive Tobacco Control Programs—

2007.” Atlanta, GA, Department of Health and Human Services, Centers for Disease Control and Prevention, 

National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2007. 

10 U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon 

General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 

2004.

11 Fiore MC, Jaén CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice 

Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008, 

available at http://www.ncbi.nlm.nih.gov/books/NBK63952. 
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smoking-cessation treatment can successfully overcome their tobacco dependence;12 however, 

“studies show that many hospitals do not consistently provide cessation services to their 

patients.”13 Evidence also suggests that tobacco cessation treatment does not increase, and may 

even decrease, the risk of re-hospitalization for tobacco users hospitalized with psychiatric 

illnesses.14 Research further demonstrates that effective tobacco cessation support across the 

care continuum can be provided with only minimal additional provider effort and without harm 

to the mental health recovery process.15

TOB-3 (NQF #1656) is a chart-abstracted measure that identifies those patients 18 years 

of age and older who have used tobacco products within 30 days of admission and who “were 

referred to or refused evidence-based outpatient counseling AND received or refused a 

prescription for FDA-approved cessation medication upon discharge.”16 TOB-3a is a subset of 

TOB-3 and identifies those IPF “patients who were referred to evidence-based outpatient 

counseling AND received a prescription for FDA-approved cessation medication upon discharge 

as well as those who were referred to outpatient counseling and had reason for not receiving a 

prescription for medication.”17 Providers must report this measure set as “an overall rate which 

includes all patients to whom tobacco treatment was provided, or offered and refused, at the time 

of hospital discharge (TOB-3), and a second rate, a subset of the first, which includes only those 

 

12 Prochaska, JJ, et al. “Efficacy of Initiating Tobacco Dependence Treatment in Inpatient Psychiatry: A 

Randomized Controlled Trial.” Am. J. Pub. Health. 2013 August 15; e1-e9.

13 Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission’s New Tobacco Cessation 

Measures – Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174, available at 

http://www.nejm.org/doi/full/10.1056/nejmp1115176.

14 Prochaska, JJ, et al. “Efficacy of Initiating Tobacco Dependence Treatment in Inpatient Psychiatry: A 

Randomized Controlled Trial.” Am. J. Pub. Health. 2013 August 15; e1-e9.

15 Ibid.

16 TOB-3 and TOB-3a Measure Specifications, available at 

http://www.jointcommission.org/assets/1/6/HIQR_Jan2015_v4_4a_1_EXE.zip

17 Ibid.
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patients who received tobacco use treatment at discharge. (TOB-3a).”18 For more information on 

the measure specifications, we refer readers to the Specifications Manual for National Hospital 

Inpatient Quality Measures at 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQn

etTier4&cid=1228773989482. Providing counseling and recommending cessation medication 

are core strategies of the Treating Tobacco Use and Dependence Guidelines.19 For the reasons 

stated above, we believe that adoption of the TOB-3/TOB-3a measure set, which assesses IPFs’ 

offering of these tobacco use cessation treatments to IPF patients, would result in better overall 

health outcomes for IPF patients. 

Furthermore, the adoption of this measure set would strengthen related measures already 

in place in the IPFQR Program. Currently, the IPFQR Program includes 2 other tobacco 

cessation measures: (1) Tobacco Use Screening (TOB-1), a chart-abstracted measure that 

assesses hospitalized patients who are screened within the first 3 days of admission for tobacco 

use (cigarettes, smokeless tobacco, pipe, and cigar) within the previous 30 days; and (2) The 

Tobacco Use Treatment Provided or Offered (TOB-2), which includes the subset, Tobacco Use 

Treatment (TOB-2a). TOB-2/TOB-2a is a chart-abstracted measure set reported as an overall 

rate that includes all patients to whom tobacco use treatment was provided, or offered and 

refused, and a second rate, a subset of the first, which includes only those patients who received 

tobacco use treatment. TOB-1 and TOB-2/TOB-2a provide a picture of care given during the 

 

18 TOB-3 and TOB-3a Measure Specifications, available at 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=12287

73989482.

19

 See Fiore MC, Jaén CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice 

Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008. 

Available at http://www.ncbi.nlm.nih.gov/books/NBK63952. The specific strategy is further specified in Strategy 

4A. 
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hospital stay. In contrast, TOB-3/TOB-3a present the care given at discharge. Together, these 3

measures/measure sets present a broader picture of the entire episode of care. If the TOB3/TOB-3a measure set is adopted, the IPFQR Program’s measure set would showcase both the 

facility’s practice of screening patients for tobacco use and the outcomes of a facility’s practice 

of offering opportunities to stop during the course of the stay and upon discharge. Further, the 

adoption of TOB-3/TOB-3a could alert IPFs to gaps in treatment for smoking cessation 

intervention at discharge if rates for these measures are low. This knowledge would support the 

development of quality improvement plans and better engage patients in treatment. 

We believe that public reporting of this information would provide consumers and other 

stakeholders with useful information in choosing among different facilities for patients who use 

tobacco products. In addition, this measure set promotes the National Quality Strategy priority 

of Effective Prevention and Treatment, particularly with respect to the leading causes of 

mortality, starting with cardiovascular disease. As noted above, tobacco use is one of the 

greatest contributors of morbidity and mortality in the United States,20 contributing to various 

forms of cardiovascular disease, among many other conditions.21 “Tobacco use remains the 

chief preventable cause of illness and death in our society.” 22 Cessation interventions can 

 

20 Centers for Disease Control and Prevention. Annual Smoking-Attributable Mortality, Years of Potential Life Lost, 

and Productivity Losses—United States, 2000-2004." Morb Mortal Wkly Rep. 2008. 57(45): 1226-1228. Available 

at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm5745a3.htm.

21 U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon 

General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 

2004.

22 Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission’s New Tobacco Cessation 

Measures – Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174 Available at:

http://www.nejm.org/doi/full/10.1056/nejmp1115176.
CMS-1627-P 123

significantly reduce the risk of developing tobacco-related disease,23 leading to decreases in 

cardiovascular disease, among other diseases, and, ultimately, mortality. Encouraging 

intervention would promote effective treatment of tobacco use, and may contribute to prevention 

of the many diseases that are associated with tobacco use. 

For these reasons, we included TOB-3/TOB-3a in our “List of Measures under 

Consideration for December 1, 2014.” The MAP provided input on the measure set and 

supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP PreRulemaking Deliberations 2015” available at 

http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=78711. 

Moreover, this measure set is NQF-endorsed for the IPF setting in conformity with the statutory 

criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We invite public comments on our proposal to adopt the TOB-3 and TOB-3a measure set 

for the FY 2018 payment determination and subsequent years. 

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief 

Intervention (NQF #1663)

Individuals with mental health conditions experience substance use disorders (SUDs) at a 

much higher rate than the general population. Individuals with the most serious mental illnesses 

have the highest rates of SUDs. Co-occurring SUDs often go undiagnosed and, without 

treatment, contribute to a longer persistence of disorders, poorer treatment outcomes, lower rates 

of medication adherence, and greater impairments to functioning. 

 

23 U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon 

General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and 

Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 

2004.
CMS-1627-P 124

Substance abuse, particularly alcohol abuse, is a significant problem in the elderly. 

Alcohol use disorders are the most prevalent type of addictive disorder in individuals ages 65 

and over.24 Roughly 6 percent of the elderly are considered to be heavy users of alcohol.25 

Alcohol abuse is often associated with depression and contributes to the etiology of many serious 

medical conditions, including liver disease and cardiovascular disease. For these reasons, it is 

important to assess IPFs’ efforts to offer alcohol abuse treatment to those patients who screen 

positive for alcohol abuse. 

SUB-2 includes “[p]atients 18 years of age and older who screened positive for unhealthy 

alcohol use who received or refused a brief intervention during the hospital26 stay.”27 SUB-2a 

includes “[p]atients who received the brief intervention during the hospital stay.”28 The measure 

set is chart-abstracted and “is reported as an overall rate which includes all patients to whom a 

brief intervention was provided, or offered and refused, and a second rate, a subset of the first, 

which includes only those patients who received a brief intervention.”29 For more information 

on the measure specifications, we refer readers to the Specifications Manual for National 

Hospital Inpatient Quality Measures at 

 

24 Ross, S. (2005). Alcohol Use Disorders in the Elderly. Primary Psychiatry, 12(1):32-40.

25 AL Mirand and JW Welte. Alcohol consumption among the elderly in a general population, Erie County, New 

York. Am J Public Health. 1996 July; 86(7): 978–984.

26 Although the measure refers to “hospitals,” the measure is specified for all in-patient settings. 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=12287

73989482.

27 SUB-2 and SUB-2a Measure Specifications, available at 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=12287

73989482.

28 Ibid.

29 SUB-2 and SUB-2a Measure Specifications, available at 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQnetTier4&cid=12287

73989482.
CMS-1627-P 125

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQn

etTier4&cid=1228773989482.

We believe that the addition of the SUB-2/SUB-2a measure set to the related existing 

substance abuse measure in the IPFQR Program would improve the overall quality of care that 

patients receive in IPF settings, as well as overall patient health outcomes. We previously 

adopted the SUB-1 measure (Alcohol Use Screening (SUB-1) (NQF #1661)) (78 FR 50890 

through 50892). SUB-1 assesses “hospitalized patients 18 years of age and older who are

screened during the hospital stay using a validated screening questionnaire for unhealthy alcohol 

use.” SUB-1 alone does not provide a full picture of an IPF’s response to this screening. 

However, when linked to SUB-2/SUB-2a, the IPF measure set depicts the rate at which patients 

are screened for potential alcohol abuse and the rate at which those who screen positive accept 

the offered interventions. Further, the adoption of SUB-2/SUB 2a could alert IPFs to gaps in 

treatment for interventions if rates are low, which supports the development of quality 

improvement plans and better patient engagement in treatment. In addition, data for the SUB2/SUB-2a measure set, in combination with the SUB-1 measure, would afford consumers useful 

information in choosing among different facilities, particularly for patients who may require 

assistance with unhealthy alcohol use. 

Additionally, we believe that this measure set promotes the National Quality Strategy 

priority of Effective Prevention and Treatment for the leading causes of mortality, starting with 

cardiovascular disease. As noted above, alcohol use disorders are the most prevalent type of 

addictive disorder in individuals ages 65 and over30 and contribute to serious medical conditions, 

 

30

 Stephen Ross. Alcohol Use Disorders in the Elderly. Psychiatry Weekly (no date). Available at: 

http://www.psychweekly.com/aspx/article/ArticleDetail.aspx?articleid=19.
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including cardiovascular disease and liver disease. Encouraging interventions would promote 

treatment of unhealthy alcohol use and may contribute to prevention of the many diseases that 

are associated with alcohol abuse, including cardiovascular disease. 

For these reasons, we included the SUB-2/SUB-2a measure set in our “List of Measures 

under Consideration for December 1, 2014.” The MAP provided input on the measure set and 

supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP PreRulemaking Deliberations 2015” available at 

http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=78711. 

Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory 

criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We invite public comments on our proposal to adopt the SUB-2/SUB-2a measure set for 

the FY 2018 payment determination and subsequent years.

3. Transition Record with Specified Elements Received by Discharged Patients (Discharges 

from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647) and 

Removal of HBIPS-6

Effective and timely communication of a patient’s clinical status and other relevant 

information at the time of discharge from an inpatient facility is essential for supporting 

appropriate continuity of care. Establishment of an effective transition from one treatment 

setting to another is enhanced by providing patients and their caregivers with sufficient 

information regarding treatment during hospitalization. Receiving discharge instructions can 

assist the patient in understanding how to maintain and enhance his/her care when discharged to 

home or any other site, and studies have shown that readmissions can be prevented by providing 
CMS-1627-P 127

detailed, personalized information to patients pre-discharge.31 

The Transition Record with Specified Elements Received by Discharged Patients 

(Discharges from on Inpatient Facility to Home/Self Care or Any other Site of Care) measure is a 

chart-abstracted measure that captures the “[p]ercentage of patients, regardless of age, 

discharged from an inpatient facility to home or other site of care, or their caregiver(s), who 

received a transition record (and with whom a review of all included information was 

documented) at the time of discharge.”32 At a minimum, the transition record should include: 

 Reason for inpatient admission;

 Major procedures and tests performed during inpatient stay and summary of results;

 Principal diagnosis at discharge;

 Current medication list;

 Studies pending at discharge;

 Patient instructions;

 Advance directive or surrogate decision maker documented or reason for not providing 

advance care plan;

 24-hour/7-day contact information, including physician for emergencies related to 

inpatient stay;

 Contact information for obtaining results of studies pending at discharge;

 Plan for follow-up care; and 

 

31 Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization.

Ann Intern Med 2009; 150:178-187.

32 Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient 

Facility to Home/Self Care or Any Other Site of Care) Measure Specifications. Available at 

http://www.qualityforum.org/Qps/0647. 
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 Primary physician, other health care professional, or site designated for follow-up care.33

The measure was developed by the American Medical Association–convened Physician 

Consortium for Performance Improvement (AMA-convened PCPI), “a national, physician-led 

initiative dedicated to improving patient health and safety.”34 For more information on this 

measure, including its specifications, we refer the readers to the AMA-convened PCPI list of 

measures at http://www.qualityforum.org/Qps/0647. 

The Transition Record with Specified Elements Received by Discharged Patients 

(Discharges from an Inpatient Facility to Home/Self Care or Any other Site of Care) measure 

seeks to prevent gaps in care transitions caused by the patient receiving inadequate or insufficient 

information that lead to avoidable adverse events and cost CMS approximately $15 billion due to 

avoidable patient readmissions.35 

We believe that public reporting of this measure would afford patients and their families 

or caregivers useful information in choosing among different facilities and would promote the 

National Quality Strategy priority of Communication and Care Coordination. As articulated by 

HHS, “Care coordination is a conscious effort to ensure that all key information needed to make 

clinical decisions is available to patients and providers. It is defined as the deliberate 

organization of patient care activities between 2 or more participants involved in a patient’s care 

 

33 Ibid. 

34 See http://www.ama-assn.org/ama/pub/physician-resources/physician-consortium-performanceimprovement/about-pcpi.page? The AMA-PCPI “is nationally recognized for measure development, specification 

and testing of measures, and enabling use of measures in electronic health records (EHRs) . . . [the organization] 

develops, tests, implements and disseminates evidence-based measures that reflect the best practices and best 

interest of medicine . . .” 

35 Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June

2007. Available at: http://www.medpac.gov/documents/reports/Jun07_EntireReport.pdf.
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to facilitate appropriate delivery of health care services.”36 This proposed measure would 

promote appropriate care coordination by specifying that patients discharged from an inpatient 

facility receive relevant and meaningful transition information. This measure also would 

promote Person and Family Engagement, “a set of behaviors by patients, family members, and 

health professionals and a set of organizational policies and procedures that foster both the 

inclusion of patients and family members as active members of the health care team and 

collaborative partnerships with providers and provider organizations.”37 This proposed measure 

would inform patients of their status at discharge, empowering them to become active members 

in their care. Additionally, the inclusion in this measure of an advance care plan would support 

open communication of the patient’s, and his/her caregiver’s/surrogate’s, wishes, resulting in 

improved patient-provider communication.

For these reasons, we included this measure in our “List of Measures under Consideration 

for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in 

the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 

2015” available at 

http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=78711. In 

addition, the MAP had previously suggested this measure as one that could fill a gap in 

communication between the provider and patient at discharge38 and recommended that the 

measure be used for dual eligible patients (that is, patients with both Medicare and Medicaid 

 

36 US DHHS. “National Healthcare Disparities Report 2013.” Available at: 

http://www.ahrq.gov/research/findings/nhqrdr/nhdr13/chap7.html.

37 Guide to Patient and Family Engagement: Environmental Scan Report. May 2012. Agency for Healthcare 

Research and Quality. Rockville, MD. Available at: http://www.ahrq.gov/research/findings/finalreports/ptfamilyscan/ptfamily1.html.

38 http://www.qualityforum.org/Publications/2012/10/MAP_Families_of_Measures.aspx.
CMS-1627-P 130

coverage), who comprise a significant beneficiary population served within IPFs.39 Moreover, 

this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for

measure selection under section 1886(s)(4)(D)(i) of the Act.

If finalized, we propose that this measure would replace the existing HBIPS-6 PostDischarge Continuing Care Plan measure.40

 We believe that the Transition Record with 

Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care) measure is a more effective and robust measure than 

HBIPS-6 for use in the IPF setting. Specifically, HBIPS-6 requires discharge plans to only have 

4 components: 

 Reason for hospitalization;

 Principal diagnosis;

 Discharge medications; and

 Next level of care recommendations.41 

In contrast, the Transition Record with Specified Elements Received by Discharged Patients 

(Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure 

requires additional elements, including those described below, which are intended to improve 

quality of care, decrease costs, and increase beneficiary engagement. 

First, the proposed measure requires the provider to communicate both studies pending at 

discharge as well as contact information so that patients or their families can obtain the results of 

 

39http://www.qualityforum.org/Publications/2014/08/2014_Input_on_Quality_Measures_for_Dual_Eligible_Benefic

iaries.aspx.

40 In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-6, beginning with the FY 2014 payment 

determination (77 FR 53650-53651). We refer readers to that rule for a detailed discussion of this measure.

41 See https://manual.jointcommission.org/releases/TJC2014A1/.
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those studies. Approximately 40 percent of discharged patients have test results that are pending 

and about a quarter of such test results require further action that, if not taken in a timely manner, 

could result in potentially avoidable negative outcomes.42 HBIPS-6 does not require providers to 

specify studies pending at discharge. 

Second, the transition record is also required to contain a list of major procedures and 

tests that were performed during the hospitalization and summary results. HBIPS-6 does not 

include this requirement. We believe it is important for a patient to understand which tests were 

performed on him/her and for what purpose, understanding the outcome and consequences of 

these tests. This knowledge may serve to empower patients to seek additional care or follow-up 

when necessary, reducing the risk of avoidable consequences and readmissions. 

Third, the transition record in the proposed measure is required to include patient 

instructions while HBIPS-6 has no such requirement. Without instructions, the patient may not 

take the necessary steps for recovery, leading to complications and/or readmissions.

Fourth, the proposed measure requires both of the following: (1) 24-hour/7-day contact 

information including physicians for emergencies related to inpatient stay; and (2) the primary 

physician, other health care professional, or sites designated for follow-up care. HBIPS-6 does 

not have these requirements. Again, this information can lead to reduced complications and an 

increased likelihood of appropriate follow-up care, resulting in reduced readmissions. 

Finally, the elements required for the proposed transition record measure are far better 

aligned than HBIPS-6 with the elements required in the Summary of Care record required by the 

Electronic Health Record (EHR) Incentive Program for eligible hospitals and critical access 

 

42 Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital 

based and primary care physicians: implications for patient safety and continuity of care. JAMA

2007;297(8):831-841.
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hospitals and with the guidance on discharge planning provided by the Medicare Learning 

Network available at https://www.cms.gov/Outreach-and-Education/Medicare-LearningNetwork-MLN/MLNProducts/Downloads/Discharge-Planning-Booklet-ICN908184.pdf. 

In summary, we believe that the Transition Record with Specified Elements Received by 

Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site 

of Care) measure is more robust than HBIPS-6 because it includes these and other elements that 

are currently absent from HBIPS-6. Therefore, we propose to adopt the Transition Record with 

Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care) measure for the FY 2018 payment determination and 

subsequent years, and, if adopted, to remove HBIPS-6. We invite public comments on these 

proposals.

4. Timely Transmission of Transition Record (Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care) (NQF #0648) and removal of HBIPS-7

The literature shows infrequent communication between hospital physicians and primary 

care practitioners and that the availability of discharge summaries at the patient’s first postdischarge visit with the primary care practitioner is low, which affects the quality of care 

provided to patients.43 The Timely Transmission of Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or Any Other Site of Care) measure (NQF #0648) is a chartabstracted measure developed by AMA-convened PCPI to narrow gaps in care transition that 

result in adverse health outcomes for patients and cost CMS about $15 billion due to 

 

43 Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital 

based and primary care physicians: implications for patient safety and continuity of care. JAMA

2007;297(8):831-841.
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readmissions,44 as discussed above. This measure captures the “[p]ercentage of patients, 

regardless of age, discharged from an inpatient facility to home or any other site of care for 

whom a transition record was transmitted to the facility or primary physician or other health care 

professional designated for follow-up care within 24 hours of discharge.”45 For more 

information on this measure, including its specifications, we refer the readers to 

http://www.qualityforum.org/Qps/0648. 

We believe that public reporting of this measure will afford consumers, and their families 

or caregivers, useful information in choosing among different facilities because it communicates 

how quickly a summary of the patient’s record will be transmitted to his or her other treating 

facilities and physicians, improving care, as outlined above. We further believe that this measure 

will promote the National Quality Strategy priority of Communication and Care Coordination. 

As discussed above, according to HHS, “Care coordination is a conscious effort to ensure that all

key information needed to make clinical decisions is available to patients and providers. It is 

defined as the deliberate organization of patient care activities between 2 or more participants 

involved in a patient’s care to facilitate appropriate delivery of health care services.”46 This 

proposed measure enables a patient’s primary care physician or other healthcare practitioner to 

timely receive a transition record of the inpatient hospitalization. 

For these reasons, we included this measure in our “List of Measures under Consideration 

for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in 

 

44 Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June

2007. Available at: http://www.medpac.gov/documents/reports/Jun07_EntireReport.pdf.

45 Timely Transmission of Transition Record (Discharged from Inpatient Facility to Home/Self Care or Any Other 

Site of Care), available at http://www.ama-assn.sorg/apps/listserv/x-check/qmeasure.cgi?submit=PCPI

46 US DHHS. “National Healthcare Disparities Report 2013.” Available at: 

http://www.ahrq.gov/research/findings/nhqrdr/nhdr13/chap7.html.
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the IPFQR Program 

(http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=78711). In 

addition, the MAP had previously suggested this measure as one that could fill a gap in 

communication47 and recommended that the measure be used for dual eligible patients (that is, 

patients with both Medicare and Medicaid coverage), who comprise a significant beneficiary 

population served within IPFs.48 Moreover, this measure set is NQF-endorsed for the IPF 

setting, in conformity with the statutory criteria for measure selection under section 

1886(s)(4)(D)(i) of the Act.

If finalized, we propose that this measure would replace the existing HBIPS-7 Post 

Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge 

measure.49 HBIPS-7 requires that the continuing care plan be transmitted to the next care 

provider no later than the fifth day post discharge.50 The Timely Transmission of Transition 

Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) 

measure requires transmission to the next level of care within 24 hours of discharge. More 

timely communication of vital information regarding the inpatient hospitalization results in better 

care, reduction of systemic medical errors, and improved patient outcomes. Studies show that 

the risks of re-hospitalization are lower when primary care providers have access to patients’ 

post-discharge records at the first post-discharge visit,51,52 which may be within a day (or days) 

 

47 http://www.qualityforum.org/Publications/2012/10/MAP_Families_of_Measures.aspx.

48http://www.qualityforum.org/Publications/2014/08/2014_Input_on_Quality_Measures_for_Dual_Eligible_Benefic

iaries.aspx.

49 In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-7 Post Discharge Continuing Care Plan 

Transmitted to the Next Level of Care Provider Upon Discharge, beginning with the FY 2014 payment 

determination (77 FR 53651-53652). We refer readers to that rule for a detailed discussion of this measure.

50 https://manual.jointcommission.org/releases/TJC2014A1/.

51 van Walraven C, Seth R, Austin PC, Laupacis A. (2002). Effect of discharge summary availability during 

postdischarge visits on hospital readmission. Journal of General Internal Medicine 17:186–192.
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of discharge. Critically, the availability of the discharge record to the next level provider within 

24 hours after discharge supports more effective care coordination and patient safety, since a 

delay in communication can result in medication or treatment errors. Thus, we believe that 

replacing HBIPS-7 with the Timely Transmission of Transition Record (Discharges from an 

Inpatient Facility to Home/Self Care or Any Other Site of Care) measure would increase the 

quality of care provided to patients, reduce avoidable readmissions, and increase patient safety.

We invite public comments on our proposals to adopt the Timely Transmission of 

Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of 

Care) measure for the FY 2018 payment determination and subsequent years and, if adopted, our 

removal of HBIPS-7.

5. Screening for Metabolic Disorders 

Studies show that both second generation antipsychotics (SGAs) and antipsychotics 

increase the risk of metabolic syndrome.53 Metabolic syndrome involves a cluster of conditions 

that occur together, including excess body fat around the waist, high blood sugar, high 

cholesterol, and high blood pressure, and increases the risk of coronary artery disease, stroke, 

and type 2 diabetes. Recognizing this problem, in February 2004, the American Diabetes 

Association (ADA), the American Psychiatric Association (APA), the American Association of 

Clinical Endocrinologists, and the North American Association for the Study of Obesity released 

a consensus statement finding that the use of SGAs “have been associated with reports of 

 

52

 Jack BW, Chetty VK, Anthony D, et al. (2009). A reengineered hospital discharge program to decrease 

rehospitalization. Ann Intern Med.150(3),178-187.

53 The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North 

American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs 

and obesity and diabetes. Diabetes Care, 27, 596-601. Marder, Stephen R., M.D., et al. Physical Health Monitoring 

of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49. 
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dramatic weight gain, diabetes (even acute metabolic decompensation, for example, diabetic 

ketoacidosis [DKA]), and an atherogenic lipid profile (increased LDL cholesterol and 

triglyceride levels and decreased HDL cholesterol) . . . [and] [s]ubsequent drug surveillance and 

retrospective database analyses suggest that there is an association between specific SGAs and 

both diabetes and obesity.”54 SGAs also have an effect on serum lipids and could result in 

dyslipidemia.55 Given these concerns, the group recommended that “baseline screening 

measures be obtained before, or as soon as clinically feasible after, the initiation of any 

antipsychotic medication,” including body mass index (BMI), blood pressure, fasting plasma 

glucose, and fasting lipid profile.56 Although the consensus statement specifically discussed the 

issues with SGAs, the ADA also emphasized that “all patients receiving antipsychotic 

medications [should] be screened”57 and subsequent studies have found that “[i]n schizophrenic 

patients, the level of lipid profile had been increased in both atypical and conventional 

antipsychotic users”58

Numerous other organizations have also made similar recommendations.59 For example, 

the National Association of State Mental Health Program Directors Medical Directors Council 

 

54 The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North 

American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs 

and obesity and diabetes. Diabetes Care, 27, 596-601.

55 Ibid. 

56 Ibid.

57 The American Diabetes Association (2006). Antipsychotic Medications and the Risk of Diabetes and 

Cardiovascular Disease. Available at: 

http://professional.diabetes.org/admin/UserFiles/file/CE/AntiPsych%20Meds/Professional%20Tool%20%231(1).pdf

(emphasis added).

58 Roohafsza, H, Khani, A, Afshar, H, Garakyaraghi, A, Ghodsi, B. Lipid profile in antipsychotic drug users: A 

comparative study. ARYA Atheroscler. May 2013; 9(3): 198–202 (emphasis added).

59 De Hert, M., Dekker, J.M. & Wood, D. (2009). Cardiovascular disease and diabetes in people with severe mental 

illness. Position statement from the European Psychiatric Association (EPA), supported by the European 

Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC). Eur Psychiatry, 24, 

412-424; Zolnierek, C.D. (2009). Non-psychiatric hospitalization of people with mental illnesses: A systematic 

review. Journal of Advanced Nursing, 65(8), 1570-1583.
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notes, “the second generation antipsychotic medications have become more highly associated 

with weight gain, diabetes, dyslipidemia, insulin resistance, and the metabolic syndrome.” They 

recommend the same screening as the consensus statement (BMI, blood pressure, fasting plasma 

glucose, and fasting lipid profile) and emphasize that this screening is “the standard of care for 

the general population.”60 Likewise, the Mount Sinai Conference,61 convened in 2002, 

recommended that, for every patient with schizophrenia, “regardless of the antipsychotic 

prescribed,” mental health providers should, among other things: (1) monitor and chart BMI; (2) 

measure plasma glucose levels (fasting or HbA1c); and (3) obtain a lipid profile.62 

Despite these consensus statements and guidelines, many of which are over a decade old, 

screening for metabolic syndrome remains low and there appears to be disagreement regarding 

where the responsibility for this screening lies.63 Studies show a systematic lack of metabolic 

risk monitoring of patients who have been prescribed antipsychotics.64 Screening for metabolic 

syndrome may reduce the risk of preventable adverse events and improve the physical health 

 

60 National Association of State Mental Health Program Directors Medical Directors Council (2006). Morbidity and 

mortality in people with serious mental illness. Available at: 

http://www.nasmhpd.org/docs/publications/MDCdocs/Mortality%20and%20Morbidity%20Final%20Report%208.1

8.08.pdf.

61 The Mount Sinai Conference was conferred to “focus on specific questions regarding the pharmacotherapy of 

schizophrenia . . . Participants in the conference were selected based on their knowledge of and contributions to the 

literature in this area . . . Also in attendance [were] various groups concerned with improving psychopharmacology 

in routine practice settings.” Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with 

Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

62 Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry.

2004 Aug;161(8):1334-49.

63 See e.g., Brooks, Megan. “Metabolic Screening in Antipsychotic Users: Whose Job Is It?” Medscape Medical 

News. 8 May 2012. Available at http://www.medscape.com/viewarticle/763468. Mittal D, Li C, Viverito K,

Williams JS, Landes RD, Thapa PB, Owen R. Monitoring for metabolic side effects among outpatients with 

dementia receiving antipsychotics. Psychiatr Serv. 2014 Sep 1;65(9):1147-53.

64 Nasrallah, H. A, MD (2012). There is no excuse for failing to provide metabolic monitoring for patients receiving 

antipsychotics. Current Psychiatry, 4 (citing Mitchell AJ, Delaffon V, Vancampfort D, et al.Guideline concordant 

monitoring of metabolic risk in people treated with antipsychotic medication: systematic review and meta-analysis 

of screening practices. Psychol Med. 2012;42(1):125-147.)
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status of the patient. Therefore, we believe it is necessary to include a measure of metabolic 

syndrome screening in the IPFQR Program.

The Screening for Metabolic Disorders measure is a chart-abstracted measure developed 

by CMS and defined as a percentage of discharges from an IPF for which a structured metabolic 

screening for 4 elements was completed in the past year. The denominator includes IPF patients 

discharged with one or more routinely scheduled antipsychotic medications during the 

measurement period. The numerator is the total number of patients who received a metabolic 

screening either prior to, or during, the index IPF stay. The screening must contain four tests: (1) 

BMI; (2) blood pressure; (3) glucose or HbA1c; and (4) a lipid panel—which includes total 

cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and low density lipoprotein 

(LDL-C) levels. The screening must have been completed at least once in the 12 months prior to 

the patient’s date of discharge. Screenings can be conducted either at the reporting facility or 

another facility for which records are available to the reporting facility. The following patients 

are excluded from the measure: (1) patients for whom a screening could not be completed within 

the stay due to the patient’s enduring unstable medical or psychological condition; and (2) 

patients with a length of stay equal to or greater than 365 days, or less than 3 days. In section 

F.3. below, we propose a sampling methodology for this and certain other measures.

Testing of this measure demonstrated that performance on the metabolic screening 

measure was low, on average, across the tested IPFs. The measure’s average performance rate of 

42 percent signals a strong opportunity for improvement. During testing, the metabolic 

screening measure also demonstrated nontrivial variation in performance among IPFs (6.2–98.6 

percent). In addition, it demonstrated near-perfect agreement between chart abstractors (kappa 
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of 0.93 for the measure numerator).65

We included the Screening for Metabolic Disorders measure (then titled “IPF Metabolic 

Screening”) in our “Measures Under Consideration List” in December 2013. The MAP did not 

recommend this measure, noting, “a different NQF-endorsed measure better addresses the needs 

of the program.”66 However, the different NQF-endorsed measure was not identified by the 

MAP, and we are unaware of any screening measures for metabolic syndrome that are NQFendorsed. We note that, when presented to the MAP, the denominator for this measure was the 

“total number of psychiatric inpatients admitted during the measurement period.” Based on 

testing and further feedback on the measure, we revised the measure by reducing its application 

to only those patients on antipsychotic medication; the denominator for the measure is now “IPF 

patients discharged with one or more routinely scheduled antipsychotic medications during the 

measurement period.” We believe that this change was appropriate because, as discussed above, 

the patients most at risk for metabolic syndrome are those receiving antipsychotics and the APA 

and other consensus organizations recommend this screening for patients on antipsychotics. 

Furthermore, by limiting the application of the measure only to those receiving antipsychotics, 

we believe that we have reduced provider burden, both in terms of possible changes in practice 

that might result from the measure, as well as the direct burden resulting from its collection and 

reporting. 

We believe that this measure promotes the National Quality Strategy priority of Making 

 

65 Development of Quality Measures for Inpatient Psychiatric Facilities. February 2015. U.S. Department of Health 

and Human Services, Assistant Secretary for Planning and Evaluation, Office of Disability, Aging, and Long-term 

Care Policy. Page xi, at http://aspe.hhs.gov/daltcp/reports/2015/ipf.cfm.

66 MAP 2014 Recommendations on Measures for More than 20 Federal Programs, 179, at 

http://www.qualityforum.org/Publications/2014/01/MAP_PreRulemaking_Report__2014_Recommendations_on_Measures_for_More_than_20_Federal_Programs.aspx.
CMS-1627-P 140

Care Safer, which seeks to reduce risk that is caused by the delivery of healthcare. As discussed 

above, antipsychotics have been shown to be related to metabolic syndrome. The Screening for 

Metabolic Disorders measure is aimed at the prevention and treatment of serious side effects of 

these drugs.

Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is 

not endorsed by NQF as long as due consideration is given to measures that have been endorsed 

or adopted by a consensus organization identified by the Secretary. We have been unable to 

identify any measures addressing screening for metabolic syndrome for the IPF setting that have 

been endorsed by the NQF or adopted by any other consensus organization. We believe the 

proposed measure for the Screening for Metabolic Disorders meets the measure selection 

exception requirement under section 1886(s)(4)(D)(ii) of the Act. 

We invite public comments on our proposal to adopt this measure for the FY 2018 

payment determination and subsequent years.

6. Summary of Measures Proposed for Adoption and Removal for FY 2018 and Subsequent 

Years

The measures that we are proposing to add to the IPFQR Program for the FY 2018 

payment determination and subsequent years are set forth in Table 20, below.

Table 20- IPFQR Program Measures Proposed for the FY 2018 Payment 

Determination and Subsequent Years 

National 

Quality 

Strategy 

Priority

NQF #

Measure ID Measure

Effective 

Prevention and 

Treatment

1656 TOB-3 and TOB-3a Tobacco Use Treatment Provided or 

Offered at Discharge and the subset 

measure Tobacco Use Treatment at 

Discharge

Effective 

Prevention and 

1663 SUB-2 and SUB-2a Alcohol Use Brief Intervention 

Provided or Offered and SUB-2a 
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Table 20- IPFQR Program Measures Proposed for the FY 2018 Payment 

Determination and Subsequent Years 

National 

Quality 

Strategy 

Priority

NQF #

Measure ID Measure

Treatment Alcohol Use Brief Intervention

Communication 

and Care 

Coordination; 

Person and 

Family 

Engagement

0647 N/A Transition Record with Specified 

Elements Received by Discharged

Patients (Discharges from an Inpatient 

Facility to Home/Self Care or

Any Other Site of Care) 

Communication 

and Care 

Coordination

0648 N/A Timely Transmission of Transition 

Record (Discharges from an

Inpatient Facility to Home/Self Care 

or Any Other Site of Care) 

Making Care 

Safer

N/A N/A Screening for Metabolic Disorders

The measures that we are proposing to remove beginning with the FY 2018 payment 

determination are set forth in Table 21, below.

Table 21- IPFQR Program Measures Proposed to be Removed for the FY 2018 

Payment Determination and Subsequent Years 

NQF #

Measure ID Measure

0557 HBIPS-6

Post-Discharge Continuing Care Plan 

(Removal of measure contingent upon 

adoption of proposed measure, Transition 

Record with Specified Elements Received 

by Discharged Patients (Discharges from an 

Inpatient Facility to Home/Self Care or

Any Other Site of Care)) 

0558 HBIPS-7

Post Discharge Continuing Care Plan 

Transmitted to the Next Level of Care 

Provider Upon Discharge 

(Removal of measure contingent upon 

adoption of proposed measure, Timely 

Transmission of Transition Record 

(Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care))
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If these proposals are adopted, the number of measures for the FY 2018 IPFQR Program 

would total 16, as set forth in Table 22, below. 

Table 22 – Previously Adopted and Proposed Measures for FY 2018 and Subsequent Years

NQF #

Measure ID Measure

0640

HBIPS-2 Hours of Physical Restraint Use

0641

HBIPS-3 Hours of Seclusion Use

0560 HBIPS-5 Patients Discharged on Multiple Antipsychotic 

Medications with Appropriate Justification

0576 FUH Follow-up After Hospitalization for Mental Illness

1661 SUB-1 Alcohol Use Screening

1663 SUB-2 and SUB-2a Alcohol Use Brief Intervention Provided or Offered 

and SUB-2a Alcohol Use Brief Intervention*

1651 TOB-1 Tobacco Use Screening

1654

TOB-2

TOB-2a

Tobacco Use Treatment Provided or Offered and

Tobacco Use Treatment

1656 TOB-3 and TOB-3a Tobacco Use Treatment Provided or Offered at 

Discharge and the subset measure Tobacco Use 

Treatment at Discharge*

1659 IMM-2 Influenza Immunization

0647 N/A Transition Record with Specified Elements Received 

by Discharged Patients (Discharges from an 

Inpatient Facility to Home/Self Care or Any Other 

Site of Care)*

0648 N/A Timely Transmission of Transition Record 

(Discharges from an Inpatient Facility to Home/Self 

Care or Any Other Site of Care)*

N/A N/A Screening for Metabolic Disorders*

N/A N/A Influenza Vaccination Coverage Among Healthcare 

Personnel

N/A N/A Assessment of Patient Experience of Care

N/A N/A Use of an Electronic Health Record

*Measures proposed for the FY 2018 payment determination and future years.
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E. Possible IPFQR Program Measures and Topics for Future Consideration

As we have previously indicated (79 FR 45974 through 45975), we seek to develop a 

comprehensive set of quality measures to be available for widespread use for informed decisionmaking and quality improvement in the IPF setting. Therefore, through future rulemaking, we 

intend to propose new measures that will help further our goals of achieving better health care 

and improved health for Medicare beneficiaries who obtain inpatient psychiatric services through 

the widespread dissemination and use of quality information.

We are developing a 30-day psychiatric readmission measure that is similar to the 

readmission measures currently in use for other CMS quality reporting programs, such as the 

Hospital Inpatient Quality Reporting Program. We anticipate that we will recommend additional 

measures for development or adoption in the future. We intend to develop a measure set that 

effectively assesses IPF quality across the range of services and diagnoses, encompasses all of 

the goals of the CMS quality strategy, addresses measure gaps identified by the MAP and others, 

and minimizes collection and reporting burden. We may also propose the removal of some 

measures in the future. 

We invite public comment on measures that we should consider.

F. Changes to Reporting Requirements

We are proposing to make the following changes to our reporting requirements for FY 

2017 and subsequent years:

 Requiring that measures be reported as a single yearly count rather than by quarter and age; 

and

 Requiring that aggregate population counts be reported as a single yearly number rather 
CMS-1627-P 144

than by quarter.

For FY 2018 and subsequent years we are also proposing to make one change, allowing

uniform sampling requirements for certain measures.

1. Proposed Changes to Reporting by Age and Quarter for FY 2017 Payment Determination and 

Subsequent Years

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53656), we finalized 

our policy that IPFs must submit data for chart-abstracted measures to the Web-Based Measures 

Tool on an annual basis aggregated by quarter. We also finalized our policy that IPFs must 

submit data as required by The Joint Commission, which calls for IPFs to submit data for 

measures by age group. Since then, we have learned that obtaining data for each quarter and by 

age is burdensome to providers and the resultant number of cases is often too small to allow 

public reporting. That is, we do not report data on Hospital Compare for measures with fewer 

than 11 cases; reporting by age and quarter often causes the number of cases to fall below 11. 

For example, for HBIPS-5, in Quarter 2 of 2013, only 5.75 percent of the data were reportable. 

Likewise, in Quarter 3 and Quarter 4 of 2013, for HBIPS-5, only 5.5 percent of the data were 

reportable. 

Therefore, beginning with FY 2017, we propose to require facilities to report data for 

chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather 

than by quarter, and to discontinue the requirement for reporting by age group. If adopted, we 

would require IPFs to report a single aggregate measure rate for each measure annually for each 

payment determination. 

We believe that this change would reduce provider burden because IPFs would report a 

single rate for each measure. In addition, we do not believe that quarterly data or data stratified 
CMS-1627-P 145

by age are necessary for quality improvement activities. We are able to differentiate, and the 

public is able to view on Hospital Compare, those IPFs that perform well on measures from 

those for which quality improvement activities may be necessary based on an annual aggregate 

rate submission. We note, however, that in the future, if our evolving measures set, quality 

improvement goals, and experience with the program indicate a change is needed, we may 

reevaluate and reinstate the requirement for quarterly reporting. 

In Table 23, below, we set forth the proposed quality reporting and submission timelines 

for the FY 2017 payment determination and subsequent years for all the measures except FUH 

and the Influenza Vaccination Coverage among Healthcare Personnel measures. We note that 

FUH is claims-based, and therefore does not require additional data submission. The Influenza 

Vaccination Coverage among Healthcare Personnel measure is reported to the Centers for 

Disease Control and Prevention, and we refer readers to the FY 2015 IPF PPS final rule for more 

information on the reporting timeline for this measure (79 FR 45969).

Table 23-Proposed Quality Reporting Periods and Timeframes for the FY 2017 Payment Determination 

and Subsequent Years

Payment Determination 

(FY) Reporting Period for Services Provided Data Submission Timeframe

2017 January 1, 2015-December 31, 2015 July 1, 2016 – August 15, 2016

We invite public comment on this proposal.

2. Proposed Changes to Aggregate Population Count Reporting for FY 2017 Payment 

Determination and Subsequent Years

In the FY 2015 IPF PPS final rule (79 FR 45973), we finalized our policy that IPFs must 

submit aggregate population counts for Medicare and non-Medicare discharges by age group, 

diagnostic group, and quarter, and sample size counts for measures for which sampling is 

performed. In section V.F.1. of this proposed rule, we are proposing to only require measure 
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reporting as an annual aggregate rate, rather than by quarter. Likewise, beginning with the FY 

2017 payment determination, we propose to require non-measure data to be reported as an 

aggregate, yearly count rather. We invite public comment on this proposal.

3. Proposed Changes to Sampling Requirements for FY 2018 Payment Determination and 

Subsequent Years

Measure specifications for the measures that we have adopted and propose to adopt allow 

sampling for some measures; however, for other measures, IPFs must report data for all 

discharges/patients. In addition, the sampling requirements sometimes vary by measure. In 

response to these policies, in the FY 2014 IPPS/LTCH PPS final rule, some commenters noted 

that different sampling requirements in the measures could increase burden on facilities because 

these differences would require IPFs to have varying policies and procedures in place for each 

measure (78 FR 50901). Although we stated our belief that the importance of these measures 

and of gathering information for all discharges/patients outweighs the burden of various 

sampling requirements, we now believe that the additional measures proposed in this proposed 

rule tip the balance of benefit and burden. Therefore, and for the reasons provided below, we are 

proposing to allow a uniform sampling methodology both for measures that require sampling and 

for certain other measures. Specifically, we propose to allow The Joint Commission/CMS 

Global Initial Patient Population sampling in Section 2.9_Global Initial Patient Population found 

at 

https://www.qualitynet.org/dcs/ContentServer?c=Page&pagename=QnetPublic%2FPage%2FQn

etTier4&cid=1228773989482. If this proposal is finalized, it will allow IPFs to take one, global 

sample for all measures specified in Table 24, thereby decreasing burden on these facilities and 

streamlining policies and procedures.
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In our current and proposed measure set, the measures for which we propose to allow The 

Joint Commission/CMS Global sampling would include those outlined in Table 24, below.

Table 24 - Measures to which Proposed Sampling Applies*

NQF #

Measure ID Measure

0560 HBIPS-5 Patients Discharged on Multiple Antipsychotic 

Medications with Appropriate Justification

1661 SUB-1 Alcohol Use Screening

1663 SUB-2 and SUB-2a Alcohol Use Brief Intervention Provided or Offered 

and SUB-2a Alcohol Use Brief Intervention**

1651 TOB-1 Tobacco Use Screening

1654

TOB-2

TOB-2a

Tobacco Use Treatment Provided or Offered and

Tobacco Use Treatment

1656 TOB-3 and TOB-3a Tobacco Use Treatment Provided or Offered at 

Discharge and the subset measure Tobacco Use 

Treatment at Discharge**

1659 IMM-2 Influenza Immunization

0647 N/A Transition Record with Specified Elements Received 

by Discharged Patients (Discharges from an 

Inpatient Facility to Home/Self Care or Any Other 

Site of Care)**

0648 N/A Timely Transmission of Transition Record 

(Discharges from an Inpatient Facility to Home/Self 

Care or Any Other Site of Care)**

N/A N/A Screening for Metabolic Disorders**

*Measures proposed for removal have not been included in this table. If these measures (HBIPS-4, HBIPS-6, and 

HBIPS-7) are not removed, the sampling methodology would also apply to their collection and submission.

**Measures proposed for the FY 2018 payment determination and future years.

In section F.1. of this proposed rule, we are proposing to require reporting on measures as 

a yearly count rather than by quarter. Because The Joint Commission/CMS Global sampling 

guidelines specify sampling by quarter, we propose to modify their sampling guidelines by 

multiplying the “number of cases in the initial patient population” and the “number of cases to be

sampled” by 4. In addition, since we require all IPFs to report data on all chart-abstracted 

measures even when the population size for a given measure is small or zero (78 FR 50901), we 
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have modified the table to require reporting regardless of the number of cases. Thus, we propose 

the following sampling guidelines for the measures above:

Number of cases in initial patient 

population Number of records to be sampled

> 6,117 1,224

3,057 -6,116 20% of initial patient population

609 - 3,056 609

0 - 608 All cases

As stated above, we believe this proposal will simplify processes and procedures for IPFs 

because uniform requirements will promote streamlined procedures and reporting. We also 

believe the proposal will decrease burden by allowing IPFs to identify a single, initial patient 

population for all of the measures specified in Table 24 from which to calculate the sample size. 

Furthermore, we do not believe this approach will reduce quality improvement. Sampling 

calculations ensure that enough data are represented in the sample to determine accurate measure 

rates. Therefore, even with sampling, we believe that CMS, IPFs, and the public would be able 

to differentiate those IPFs who perform well on measures from those who do not.

We invite public comment on this proposal, which would begin with the FY 2018 

payment determination.

G. Public Display and Review Requirements

We are not proposing any changes to the public display and review requirements for the 

FY 2018 payment determination and subsequent years and refer readers to the FY 2014 

IPPS/LTCH PPS final rule (78 FR 50897 through 50898) for more information.
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H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements 

We are not proposing any changes to the procedural and submission requirements for the 

FY 2018 payment determination and subsequent years and refer readers to the FY 2014 

IPPS/LTCH PPS final rule (77 FR 50898 through 50899) for more information on these 

previously finalized requirements.

2. Proposed Change to the Reporting Periods and Submission Timeframes 

In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901), we finalized requirements for 

reporting periods and submission timeframes for the IPFQR Program measures. We are 

proposing one change to these requirements, as discussed above in section V.F.1. of this 

proposed rule. Specifically, we are proposing to no longer require that measure rates be reported 

quarterly and by age, but to only require an aggregate, yearly count.

3. Population and Sampling 

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53657 through 53658) and FY 2014 

IPPS/LTCH PPS final rule (78 FR 58901 through 58902), we finalized policies for population, 

sampling, and minimum case thresholds. We are proposing one change to these policies, as 

discussed above in section V.F.3. of this proposed rule. Specifically, we are proposing to allow 

uniform sampling on certain measures.

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

We are not proposing any changes to the DACA requirements and refer readers to the FY 

2013 IPPS/LTCH PPS final rule (77 FR 53658) for more information on these requirements. 

I. Reconsideration and Appeals Procedures 

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660), we adopted a 
CMS-1627-P 150

reconsideration process, later codified at §412.434, whereby IPFs can request a reconsideration 

of their payment update reduction in the event that an IPF believes that its annual payment 

update has been incorrectly reduced for failure to meet all IPFQR Program requirements. We are 

not proposing any changes to the Reconsideration and Appeals Procedure and refer readers to the 

FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660) and the FY 2014 IPPS/LTCH 

PPS final rule (78 FR 50953) for further details on the reconsideration process.

J. Exceptions to Quality Reporting Requirements 

We are not proposing any changes to the exceptions to quality reporting requirements and 

refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53659 through 53660), where we 

initially finalized the policy as “Waivers from Quality Reporting,” and the FY 2015 IPF PPS 

final rule (79 FR 45978), where we re-named the policy as “Exceptions to Quality Reporting 

Requirements” for more information.

VI. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA), we are required to publish a 60-day 

notice in the Federal Register and solicit public comment before a collection of information 

requirement is submitted to the Office of Management and Budget (OMB) for review and 

approval.

To fairly evaluate whether an information collection should be approved by OMB, PRA 

section 3506(c)(2)(A) requires that we solicit comment on the following issues:

● The need for the information collection and its usefulness in carrying out the proper 

functions of our agency.

● The accuracy of our burden estimates.

● The quality, utility, and clarity of the information to be collected. 
CMS-1627-P 151

● Our effort to minimize the information collection burden on the affected public, 

including the use of automated collection techniques.

We are soliciting public comment on each of the section 3506(c)(2)(A)-required issues 

for the following information collection requirements (ICRs).

A. Wage Estimates

We estimate that reporting data for the IPFQR Program measures can be accomplished 

by staff with a mean hourly wage of $16.42 per hour.67 Under OMB Circular A-76, in 

calculating direct labor, agencies should not only include salaries and wages, but also “other 

entitlements” such as fringe benefits.

68

 This Circular provides that the civilian position full 

fringe benefit cost factor is 36.25 percent. Therefore, using these assumptions, we estimate an 

hourly labor cost of $22.37 ($16.42 base salary + $5.95 fringe). The following table presents the

mean hourly wage, the cost of fringe benefits (calculated at 36.25 percent of salary), and the 

adjusted hourly wage.

Occupation 

Title

Occupation 

Code

Mean Hourly 

Wage ($/hr)

Fringe Benefit 

(at 36.25% in 

$/hr)

Adjusted 

Hourly Wage 

($/hr)

Medical 

Records and 

Health 

Information 

Technician

29-2071 16.42 5.95 $22.37

The BLS is “the principal Federal agency responsible for measuring labor market 

activity, working conditions, and price changes in the economy.”69 Acting as an independent 

 

67 http://www.bls.gov/ooh/healthcare/medical-records-and-health-information-technicians.html.

68 http://www.whitehouse.gov/omb/circulars_a076_a76_incl_tech_correction.

69 http://www.bls.gov/bls/infohome.htm.
CMS-1627-P 152

agency, the Bureau provides objective information for not only the government, but also for the 

public. The Bureau’s National Occupational Employment and Wage Estimates describes 

Medical Records and Health Information Technicians as those responsible for organizing and 

managing health information data. Therefore, we believe it is reasonable to assume that these 

individuals would be tasked with abstracting clinical data for these measures. In addition, the 

Hospital IQR Program uses this wage to calculate its burden estimates.

B. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program

We refer readers to the FY 2015 IPF PPS final rule (79 FR 45978 through 45980) for a 

detailed discussion of the burden for the program requirements that we have previously adopted. 

Below, we discuss only the changes in burden resulting from the provisions in this proposed rule. 

Although we propose provisions that impact both the FY 2017 and FY 2018 payment 

determinations, all of our proposals begin to apply to facilities in FY 2016. For example, data 

collection for the proposed measures begins in FY 2016, and the changes to the reporting 

requirements take effect beginning with reporting that is required in the summer of FY 2016. 

For purposes of calculating burden, we will attribute the costs associated with the proposals to 

the year in which these costs begin; for the purposes of all of the provisions in this proposed rule, 

that year is FY 2016. 

1. Changes in Time Required to Chart-Abstract Data Based on Proposed Reporting 

Requirements

As discussed in section V.F. of this preamble, we are proposing the following 3 changes 

regarding how facilities should report data for IPFQR Program measures: (1) measures must be 

reported as a single yearly count rather than by quarter and age; (2) aggregate population counts 

must be reported as a single yearly number rather than by quarter; and (3) uniform sampling 
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would be allowed for certain measures.

We believe that these changes will lead to a decrease in burden since facilities would 

only be required to enter one aggregate number for both the numerator and denominator for each 

measure and will be allowed to pull one sample used to calculate the measures specified in Table 

24 of this preamble. Consequently, we believe that the time required to chart-abstract data for 

these measures would be reduced by 20 percent. Previously, we estimated 15 minutes to chartabstract data for each case (79 FR 45979). Because of our proposed changes to sampling and 

reporting data, we are revising the figure and now estimate 12 minutes (0.20 x 15 minutes), a 

change of -3 min or -0.05 hr.

2. Estimated Burden of IPFQR Program Proposals

In section V. of this preamble, we are proposing to adopt the following five measures:

 TOB-3 - Tobacco Use Treatment Provided or Offered at Discharge and the subset 

measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);

 SUB-2 - Alcohol Use Brief Intervention Provided or Offered and the subset measure 

SUB-2a (NQF #1663);

 Transition Record with Specified Elements Received by Discharged Patients (Discharges 

from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647);

 Timely Transmission of Transition Record (Discharges from an Inpatient Facility to 

Home/Self Care or Any Other Site of Care) (NQF #0648); and

 Screening for Metabolic Disorders.

In the same section, we are also proposing to remove the following 3 measures:

 HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications; 

 Hospital Based Inpatient Psychiatric Services (HBIPS)-6 Post-Discharge Continuing 
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Care Plan (NQF #0557), if Transition Record with Specified Elements Received by Discharged 

Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) is 

adopted; and

 HBIPS-7 Post-Discharge Continuing Care Plan Transmitted to the Next Level of Care 

Provider Upon Discharge (NQF #0558), if Timely Transmission of Transition Record

(Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF 

#0648) is adopted. 

We believe that approximately 1,61770 IPFs will participate in the IPFQR Program for 

requirements occurring in FY 2016 and subsequent years. Based on data from CY 2013, we 

believe that each facility will submit measure data on approximately 43171 cases per year. 

Therefore, we estimate that adopting five measures and removing 3 measures (for a net result of 

2 measures) will result in an increase in burden of 172.4 hours per facility (2 measures x (431 

cases/measure x 0.20 hours/case)) or 278,770.80 hours across all IPFs (172.4 hours/facility x 

1,617 facilities). The increase in costs is approximately $3,856.59 per IPF ($22.37/hour x 172.4 

hours) or $6,236,102.80 across all IPFs (278,770.80 hours x $22.37/hour).

Consistent with our estimates in the FY 2015 IPF PPS final rule (79 FR 45979), we 

believe the estimated burden for training personnel on our proposals for data collection and 

submission is 2 hours per facility or 3,234 hours (2 hours/facility x 1,617 facilities) across all 

IPFs. Therefore, the cost for this training is $44.74 ($22.37/hour x 2 hours) for each IPF or 

$72,344.58 ($22.37/hour x 3,234 hours) for all facilities.

 

70 In the FY 2015 IPF PPS final rule we estimated 1,626 IPFs and are adjusting that estimate by -9 to account for 

more recent data.

71 In the FY 2015 IPF PPS final rule we estimated 556 cases per year and are adjusting that estimate by -125 to 

account for more recent data.
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Finally, IPFs must submit to CMS aggregate population counts for Medicare and nonMedicare discharges by age group, and diagnostic group, and sample size counts for measures 

for which sampling is performed. As noted above, we are proposing five new measures 

beginning with the FY 2018 payment determination. However, because, as further described 

above, we are eliminating reporting this non-measure data by quarter for all measures, we 

believe that the addition of five measures leads to a net negligible change in burden associated 

with non-measure data collection.

C. Summary of Annual Burden Estimates for Proposed Requirements

Table 25-Proposed Annual Recordkeeping and Reporting Requirements Under OMB 

Control Number 0938-1171 (CMS-10432)

Preamble 

Section(s)

Proposed 

Action Respondents

Responses 

(per 

respondent)

Burden per 

Response 

(hours)*

Total 

Annual 

Burden 

(hours)

Labor

Cost of

Reporting

($/hr)

Total Cost

($)

V.C. Remove 

HBIPS-4

1,617

862 (431 

cases/yr x 2 

measures)

0.20 278,770.80 22.37 6,236,102.80

V. Remove 

HBIPS-6 and 

HBIPS-7

V. Add NQF # 

1656, # 

1663, # 

0647, # 

0648, and 

Screening for 

Metabolic 

Disorders

Training 1 2 3,234 72,344.58

Total -- 1,617 863 2.2 282,004.8 22.37 6,308,447.38

D. ICRs Regarding the Hospital and Health Care Complex Cost Report (CMS-2552-10)

This rule would not impose any new or revised collection of information requirements 

associated with CMS-2552-10 (as discussed under preamble section III.A.3.a.i.). Consequently, 

the cost report does not require additional OMB review under the authority of the Paperwork 

Reduction Act of 1995 (44 U.S.C. 3501 et seq.). The report’s information collection 

requirements and burden estimates are approved by OMB under control number 0938-0052.

E. Submission of PRA-Related Comments
CMS-1627-P 156

We submitted a copy of this proposed rule to OMB for its review of the rule’s 

information collection and recordkeeping requirements. The requirements are not effective until 

they have been approved by the OMB.

To obtain copies of the supporting statement and any related forms for the proposed 

collections discussed above, please visit CMS’ Web site at 

www.cms.hhs.gov/Paperwork@cms.hhs.gov, or call the Reports Clearance Office at 410–786–

1326.

We invite public comment on these potential information collection requirements. If you 

wish to comment, please submit your comments electronically as specified under the 

ADDRESSES caption of this proposed rule and identify the rule (CMS-1627-P).

PRA-related comments must be received on/by June 23, 2015.

VII. Regulatory Impact Analysis

A. Statement of Need

This proposed rule would update the prospective payment rates for Medicare inpatient 

hospital services provided by IPFs for discharges occurring during the FY beginning October 1, 

2015, through September 30, 2016. We are applying the proposed FY 2012-based IPF-specific

market basket increase of 2.7 percent, less the productivity adjustment of 0.6 percentage point as 

required by 1886(s)(2)(A)(i) of the Act, and further reduced by 0.2 percentage point as required 

by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. In this proposed rule, we propose to 

adopt an IPF-specific market basket and to update the IPF labor-related share; to adopt new 

OMB CBSA delineations for the FY 2016 IPF Wage Index; and to phase out the rural adjustment 

for 37 rural providers which would become urban providers as a result of the new CBSA 

delineations. Additionally, this rule reminds providers of the October 1, 2015 implementation of 
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the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-

CM/PCS) for the IPF prospective payment system, updates providers on the status of IPF PPS 

refinements, and proposes new quality reporting requirements for the IPFQR Program. 

B. Overall Impact 

We have examined the impact of this proposed rule as required by Executive 

Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 

on Improving Regulation and Regulatory Review (January 18, 2011), the Regulatory Flexibility 

Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, 

section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104-4), 

Executive Order 13132 on Federalism (August 4, 1999) and the Congressional Review Act 

(5 U.S.C. 804(2)).

Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of 

available regulatory alternatives and, if regulation is necessary, to select regulatory approaches 

that maximize net benefits (including potential economic, environmental, public health and 

safety effects, distributive impacts, and equity). A regulatory impact analysis (RIA) must be 

prepared for a major rules with economically significant effects ($100 million or more in any 1 

year). This proposed rule is not designated as economically “significant” under section 3(f)(1) of 

Executive Order 12866. 

We estimate that the total impact of these changes for FY 2016 payments compared to 

FY 2015 payments will be a net increase of approximately $80 million. This reflects a $95

million increase from the update to the payment rates, as well as a $15 million decrease as a 

result of the update to the outlier threshold amount. Outlier payments are estimated to decrease 

from 2.3 percent in FY 2015 to 2.0 percent of total IPF payments in FY 2016. 
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The RFA requires agencies to analyze options for regulatory relief of small entities if a 

rule has a significant impact on a substantial number of small entities. For purposes of the RFA, 

small entities include small businesses, nonprofit organizations, and small governmental 

jurisdictions. Most IPFs and most other providers and suppliers are small entities, either by 

nonprofit status or having revenues of $7.5 million to $38.5 million or less in any 1 year,

depending on industry classification (for details, refer to the SBA Small Business Size Standards 

found at http://www.sba.gov/sites/default/files/files/Size_Standards_Table.pdf), or being 

nonprofit organizations that are not dominant in their markets.

Because we lack data on individual hospital receipts, we cannot determine the number of 

small proprietary IPFs or the proportion of IPFs' revenue derived from Medicare payments. 

Therefore, we assume that all IPFs are considered small entities. The Department of Health and 

Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold 

under the RFA. 

As shown in Table 26, we estimate that the overall revenue impact of this proposed rule 

on all IPFs is to increase Medicare payments by approximately 1.6 percent. As a result, since the 

estimated impact of this proposed rule is a net increase in revenue across almost all categories of 

IPFs, the Secretary has determined that this proposed rule would have a positive revenue impact 

on a substantial number of small entities. MACs are not considered to be small entities. 

Individuals and States are not included in the definition of a small entity.

In addition, section 1102(b) of the Social Security Act requires us to prepare a regulatory 

impact analysis if a rule may have a significant impact on the operations of a substantial number 

of small rural hospitals. This analysis must conform to the provisions of section 603 of the RFA. 

For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is 
CMS-1627-P 159

located outside of a metropolitan statistical area and has fewer than 100 beds. As discussed in 

detail below, the rates and policies set forth in this proposed rule would not have an adverse 

impact on the rural hospitals based on the data of the 275 rural units and 68 rural hospitals in our 

database of 1,617 IPFs for which data were available. Therefore, the Secretary has determined 

that this proposed rule would not have a significant impact on the operations of a substantial 

number of small rural hospitals. 

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also requires that 

agencies assess anticipated costs and benefits before issuing any rule whose mandates require 

spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2015, 

that threshold is approximately $144 million. This proposed rule will not impose spending costs 

on state, local, or tribal governments in the aggregate, or by the private sector, of $144 million or 

more. 

Executive Order 13132 establishes certain requirements that an agency must meet when it 

promulgates a proposed rule (and subsequent final rule) that imposes substantial direct 

requirement costs on state and local governments, preempts state law, or otherwise has 

Federalism implications. As stated above, this proposed rule would not have a substantial effect 

on state and local governments.

C. Anticipated Effects 

We discuss the historical background of the IPF PPS and the impact of this proposed rule 

on the Federal Medicare budget and on IPFs. 

1. Budgetary Impact

As discussed in the November 2004 and May 2006 IPF PPS final rules, we applied a 

budget neutrality factor to the Federal per diem base rate and ECT rate to ensure that total 
CMS-1627-P 160

estimated payments under the IPF PPS in the implementation period would equal the amount that 

would have been paid if the IPF PPS had not been implemented. The budget neutrality factor 

includes the following components: outlier adjustment, stop-loss adjustment, and the behavioral 

offset. As discussed in the May 2008 IPF PPS notice (73 FR 25711), the stop-loss adjustment is 

no longer applicable under the IPF PPS. 

As discussed in section III.D.1.e. of this proposed rule, we are using the wage index and 

labor-related share in a budget neutral manner by applying a wage index budget neutrality factor 

to the Federal per diem base rate and ECT rate. Therefore, the budgetary impact to the Medicare 

program of this proposed rule will be due to the estimated market basket update for FY 2016 of 

2.7 percent (see section III.A.4. of this proposed rule) less the productivity adjustment of 0.6 

percentage point required by section 1886 (s)(2)(A)(i) of the Act; further reduced by the “other 

adjustment” of 0.2 percentage point under sections 1886(s)(2)(A)(ii) and 1886 (s)(3)(D) of the 

Act; and the update to the outlier fixed dollar loss threshold amount.

We estimate that the FY 2016 impact will be a net increase of $80 million in payments to 

IPF providers. This reflects an estimated $95 million increase from the update to the payment 

rates and a $15 million decrease due to the update to the outlier threshold amount to set total 

estimated outlier payments at 2.0 percent of total estimated payments in FY 2016. This estimate

does not include the implementation of the required 2 percentage point reduction of the market 

basket increase factor for any IPF that fails to meet the IPF quality reporting requirements (as 

discussed in section VII.C.4. below).

2. Impact on Providers

To understand the impact of the changes to the IPF PPS on providers, discussed in this 

proposed rule, it is necessary to compare estimated payments under the IPF PPS rates and factors 
CMS-1627-P 161

for FY 2016 versus those under FY 2015. We determined the percent change of estimated FY 

2016 IPF PPS payments to FY 2015 IPF PPS payments for each category of IPFs. In addition, 

for each category of IPFs, we have included the estimated percent change in payments resulting 

from the update to the outlier fixed dollar loss threshold amount; the updated wage index data; 

the changes to wage index CBSAs; the changes to rural adjustment payments resulting from 

changes in rural or urban status, due to CBSA changes; the proposed labor-related share; and the 

estimated market basket update for FY 2016, as adjusted by the productivity adjustment 

according to section 1886(s)(2)(A)(i), and the “other adjustment” according to sections 

1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

To illustrate the impacts of the FY 2016 changes in this proposed rule, our analysis 

begins with a FY 2015 baseline simulation model based on FY 2014 IPF payments inflated to the 

midpoint of FY 2015 using IHS Global Insight Inc.'s most recent forecast of the market basket 

update (see section III.A.4. of this proposed rule); the estimated outlier payments in FY 2015; the 

CBSA delineations for IPFs based on OMB’s MSA definitions after June 2003; the FY 2014 prefloor, pre-reclassified hospital wage index; the FY 2015 labor-related share; and the FY 2015 

percentage amount of the rural adjustment. During the simulation, the total estimated outlier 

payments are maintained at 2 percent of total IPF PPS payments.

Each of the following changes is added incrementally to this baseline model in order for 

us to isolate the effects of each change:

 The update to the outlier fixed dollar loss threshold amount;

 The FY 2015 pre-floor, pre-reclassified hospital wage index without the revised OMB 

delineations;
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 The FY 2015 updated CBSA delineations, based on OMB’s February 28, 2013 Bulletin 

No. 13-01, as described in section III.D.1.c. of this proposed rule, with the proposed blended FY 

2016 IPF wage index;

 The FY 2016 rural adjustment, accounting for changes to rural or urban status due to the 

updated CBSA delineations, including the phase-out of the rural adjustment for the IPFs 

changing from rural to urban status, as described in section III.D.1.d;

 The proposed FY 2016 labor-related share;

 The estimated market basket update for FY 2016 of 2.7 percent less the productivity 

adjustment of 0.6 percentage point reduction in accordance with section 1886(s)(2)(A)(i) of the 

Act and further reduced by the “other adjustment” of 0.2 percentage point in accordance with 

sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

Our final comparison illustrates the percent change in payments from FY 2015 (that is, 

October 1, 2014, to September 30, 2015) to FY 2016 (that is, October 1, 2015, to 

September 30, 2016) including all the changes in this proposed rule.

Table 26-IPF IMPACT Table for FY 2016 (% change in columns 3-9)

Facility by Type

Number 

of IPFs Outlier

Wage 

Index1 CBSA2

Change 

in 

Rural 

Adjustment3

Labor 

Related 

Share 

(74.9%)4

IPF 

Market 

Basket 

Update5

Total 

Percent 

Change6

(1) (2) (3) (4) (5) (6) (7) (8) (9)

All Facilities 1,617 -0.3 0.0 0.0 0.0 0.0 1.9 1.6

 Total Urban 1,274 -0.3 0.0 0.0 0.0 0.2 1.9 1.8

 Total Rural 343 -0.3 0.0 -0.2 0.2 -1.1 1.9 0.6

 Urban unit 847 -0.4 0.0 0.0 0.0 0.2 1.9 1.7

 Urban hospital 427 -0.1 -0.1 0.1 0.0 0.1 1.9 1.9

 Rural unit 275 -0.3 0.1 -0.2 0.2 -1.1 1.9 0.5

 Rural hospital 68 -0.1 0.0 -0.3 0.2 -1.0 1.9 0.7

CBSA Change

Urban to Urban 1,237 -0.3 0.0 0.0 0.1 0.2 1.9 1.8
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Rural to Rural 340 -0.3 0.0 -0.2 0.1 -1.1 1.9 0.4

Urban to Rural 3 -0.1 3.1 -0.4 16.2 -1.1 1.9 20.1

Rural to Urban 37 -0.2 0.1 2.8 -4.1 -0.9 1.9 -0.5

By Type of 

Ownership:

Freestanding IPFs

 Urban Psychiatric 

Hospitals

 Government 123 -0.3 0.1 0.0 0.0 0.1 1.9 1.8

 Non-Profit 99 -0.1 0.4 0.1 0.0 0.4 1.9 2.7

 For-Profit 205 0.0 -0.3 0.1 0.0 0.0 1.9 1.6

 Rural Psychiatric 

Hospitals

 Government 36 -0.1 0.2 -0.1 0.4 -0.8 1.9 1.5

 Non-Profit 11 -0.5 -0.6 0.0 0.0 -0.3 1.9 0.5

 For-Profit 21 0.0 0.0 -0.6 0.1 -1.3 1.9 0.1

IPF Units

 Urban

 Government 129 -0.6 -0.2 -0.1 0.0 0.3 1.9 1.2

 Non-Profit 552 -0.4 0.2 0.0 -0.1 0.3 1.9 1.9

 For-Profit 166 -0.3 -0.2 0.0 0.0 0.0 1.9 1.3

 Rural

 Government 69 -0.2 -0.1 -0.3 0.1 -1.3 1.9 0.0

 Non-Profit 142 -0.3 0.2 -0.2 0.3 -0.9 1.9 0.8

 For-Profit 64 -0.3 0.0 -0.2 0.2 -1.2 1.9 0.3

By Teaching Status:

 Non-teaching 1,420 -0.2 -0.1 0.0 0.0 -0.1 1.9 1.5

 Less than 10% 

interns and residents 

to beds 110 -0.3 0.2 -0.1 0.0 0.5 1.9 2.1

 10% to 30% 

interns and residents 

to beds 61 -0.7 0.4 -0.1 0.0 0.5 1.9 2.1

 More than 30% 

interns and residents 

to beds 26 -0.7 0.4 0.0 0.0 0.8 1.9 2.4

By Region:

 New England 108 -0.3 0.8 0.0 0.0 0.7 1.9 3.2

 Mid-Atlantic 243 -0.2 0.2 -0.1 0.0 0.6 1.9 2.4

 South Atlantic 238 -0.2 -0.3 0.1 -0.1 -0.4 1.9 0.9

 East North Central 259 -0.2 0.0 0.0 0.1 -0.2 1.9 1.6

 East South Central 160 -0.2 -0.5 0.0 -0.1 -1.1 1.9 0.0

 West North Central 141 -0.4 0.0 0.1 0.0 -0.3 1.9 1.3

 West South Central 243 -0.2 -0.5 0.0 -0.1 -0.7 1.9 0.3

 Mountain 103 -0.2 0.4 0.0 0.1 0.2 1.9 2.3

 Pacific 122 -0.4 0.5 0.0 0.1 1.3 1.9 3.4

By Bed Size:

 Psychiatric 

Hospitals
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 Beds: 0-24 83 -0.1 0.0 0.1 -0.3 -0.7 1.9 0.8

 Beds: 25-49 77 -0.1 -0.4 0.3 -0.1 -0.2 1.9 1.4

 Beds: 50-75 84 -0.1 0.0 0.0 0.1 0.0 1.9 1.9

 Beds: 76 + 251 -0.1 0.0 0.0 0.0 0.1 1.9 2.0

 Psychiatric Units

 Beds: 0-24 662 -0.4 0.0 0.0 0.0 -0.3 1.9 1.2

 Beds: 25-49 301 -0.4 0.0 0.1 0.0 0.0 1.9 1.7

 Beds: 50-75 103 -0.3 0.1 0.0 0.0 0.1 1.9 1.9

 Beds: 76 + 56 -0.4 -0.1 -0.2 0.0 0.5 1.9 1.7

1

Includes a FY 2016 IPF wage index, current CBSA delineations, and a labor-related share of 0.69294.

2

Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, and a labor-related share of 

0.69294.

3

Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, a labor-related share of 

0.69294, and a rural adjustment. Providers changing from urban to rural status will receive a 17 percent rural 

adjustment, and providers changing from rural to urban status will receive 2/3 of the 17 percent rural adjustment in 

FY 2016. For those changing from urban to rural status, the total impact shown is affected by outlier threshold 

increasing, which results in smaller outlier payments as part of total payments. For those changing from rural to 

urban status, the outlier threshold is being lowered by 2/3 of 17 percent, which results in more providers being 

eligible for outlier payments, increasing the outlier portion of their total payments.

4

Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, a labor-related share of 

0.749, and a rural adjustment.

5This column reflects the payment update impact of the IPF-specific market basket update of 2.7 percent, a 0.6 

percentage point reduction for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act, and a 

0.2 percentage point reduction in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

6

Percent changes in estimated payments from FY 2015 to FY 2016 include all of the changes presented in this 

proposed rule. Note, the products of these impacts may be different from the percentage changes shown here due to 

rounding effects.

3. Results

Table 26 above displays the results of our analysis. The table groups IPFs into the 

categories listed below based on characteristics provided in the Provider of Services (POS) file, 

the IPF provider specific file, and cost report data from HCRIS:

 Facility Type

 Location

 Teaching Status Adjustment

 Census Region

 Size

The top row of the table shows the overall impact on the 1,617 IPFs included in this analysis.
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In column 3, we present the effects of the update to the outlier fixed dollar loss threshold 

amount. We estimate that IPF outlier payments as a percentage of total IPF payments are 2.3

percent in FY 2015. Thus, we are adjusting the outlier threshold amount in this proposed rule to 

set total estimated outlier payments equal to 2 percent of total payments in FY 2016. The 

estimated change in total IPF payments for FY 2016, therefore, includes an approximate 0.3

percent decrease in payments because the outlier portion of total payments is expected to 

decrease from approximately 2.3 percent to 2.0 percent. 

The overall impact of this outlier adjustment update (as shown in column 3 of Table 

26), across all hospital groups, is to decrease total estimated payments to IPFs by 0.3 percent. 

The largest decrease in payments is estimated to reflect a 0.7 percent decrease in payments for 

IPFs located in teaching hospitals with an intern and resident Average Daily Census (ADC) ratio 

that is 10 percent or greater. 

In column 4, we present the effects of the budget-neutral proposed update to the IPF 

wage index. This represents the effect of using the most recent wage data available without 

taking into account the revised OMB delineations, which are presented separately in the next 

column. That is, the impact represented in this column is solely that of updating from the FY 

2015 IPF wage index to the FY 2016 IPF wage index without any changes to the OMB 

delineations. We note that there is no projected change in aggregate payments to IPFs, as 

indicated in the first row of column 4. However, there will be distributional effects among 

different categories of IPFs. For example, we estimate the largest increase in payments to be 3.1

percent for IPFs changing from urban to rural status, and the largest decrease in payments to be 

0.6 percent for rural non-profit freestanding IPFs.
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In column 5, we present the effects of the new OMB delineations and the proposed 

transition to the new delineations using the transitional IPF wage index. The FY 2016 IPF 

proposed transitional wage index is a blended wage index using 50 percent of the IPF’s FY 2016 

wage index based on the new OMB delineations and 50 percent of the IPF’s FY 2016 wage 

index based on the OMB delineations used in FY 2015. In the aggregate, since these proposed 

updates to the wage index are applied in a budget-neutral manner, we do not estimate that these 

proposed updates would affect overall estimated payments to IPFs. However, we estimate that 

these proposed updates would have distributional effects. We estimate the largest increase in 

payments would be 2.8 percent for IPFs changing from rural to urban status and the largest 

decrease in payments would be 0.6 percent for rural for-profit freestanding IPFs. 

In column 6, we present the effects of the changes to the rural adjustment under the new

CBSA delineations. There are 3 urban IPFs which would be newly designated as rural IPFs, 

which would now receive a full 17 percent rural adjustment. We estimate that the largest 

increase in payments would be to these 3 newly-rural IPFs. Note that each column’s simulations 

include both regular and outlier payments; as regular payments increase, outlier payments 

decrease to maintain outlier payments at 2 percent of total payments. As such, the increase to 

total IPF payments is estimated to be 16.2 percent. There are also 37 rural IPFs which would be 

newly designated as urban IPFs, where we proposed to phase out their rural adjustment over 3 

years. These 37 newly-urban providers would receive 2/3 of the 17 percent rural adjustment in 

FY 2016, 1/3 of the 17 percent rural adjustment in FY 2017, and no rural adjustment for FY 

2018 and subsequent years. As the regular payments for these 37 providers decrease, their 

outlier payments increase to maintain outlier payments at 2 percent of total payments. We 
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estimate that the largest decrease in payments would be 4.1 percent for these 37 newly-urban 

providers. 

In column 7, we present the estimated effects of the proposed labor-related share. The 

proposed update to the IPF labor-related share is made in a budget-neutral manner and therefore 

would not affect total estimated IPF PPS payments. However, it would affect the estimated 

distribution of payments among providers. For example, we estimate the largest increase in 

payments would be 1.3 percent to IPFs in the Pacific region. We estimate the largest decrease in 

payments would be 1.3 percent to rural for-profit freestanding IPFs and to rural IPF 

governmental units. 

In column 8, we present the estimated effects of the update to the IPF PPS payment rates

of 1.9 percent, which are based on a proposed 2.7 percent IPF-specific market basket update, less 

the productivity adjustment of 0.6 percentage point in accordance with section 1886(s)(2)(A)(i), 

and further reduced by 0.2 percentage point in accordance with section 1886(s)(2)(A)(ii) and 

1886(s)(3)(D). 

Finally, column 9 compares our estimates of the total changes reflected in this proposed 

rule for FY 2016 to the payments for FY 2015 (without these changes). This column reflects all 

proposed FY 2016 changes relative to FY 2015. The average estimated increase for all IPFs is 

approximately 1.6 percent. This estimated net increase includes the effects of the estimated 2.7

percent market basket update reduced by the productivity adjustment of 0.6 percentage point, as 

required by section 1886(s)(2)(A)(i)of the Act and further reduced by the “other adjustment” of 

0.2 percentage point, as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. It 

also includes the overall estimated 0.3 percent decrease in estimated IPF outlier payments as a 

percent of total payments from the update to the outlier fixed dollar loss threshold amount. Since 
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we are making the updates noted in columns 4 through 7 in a budget-neutral manner, they will 

not affect total estimated IPF payments in the aggregate. However, they will affect the estimated 

distribution of payments among providers. 

Overall, urban IPFs are estimated to experience a 1.8 percent increase in payments in FY 

2016 and rural IPFs are estimated to experience a 0.6 percent increase in payments in FY 2016. 

The largest estimated decrease in payments is 0.5 percent for rural IPFs that transition to urban 

status as a result of the new OMB delineations. As noted previously, we proposed to mitigate 

the effects of the loss of the rural adjustment to these 37 providers by phasing the adjustment out 

over 3 years. The largest payment increase is estimated at 20.1 percent for IPFs that transition

from urban to rural status (thereby gaining the 17 percent rural adjustment), followed by a 3.4

percent increase for IPFs in the Pacific region. 

4. Effects of Updates to the IPFQR Program

As discussed in section V. of this proposed rule and in accordance with section 

1886(s)(4)(A)(i) of the Act, we will implement a 2 percentage point reduction in the FY 2018 

market basket update for IPFs that have failed to comply with the IPFQR Program requirements

for FY 2018, including reporting on the required measures. In section V. of this proposed rule, 

we discuss how the 2 percentage point reduction will be applied. For FY 2015, of the 1,725 IPFs 

eligible for the IPFQR Program, 31 IPFs (1.8 percent) did not receive the full market basket 

update because of the IPFQR Program; 10 of these IPFs chose not to participate and 21 did not 

meet the requirements of the program. We anticipate that even fewer IPFs would receive the 

reduction for FY 2016 as IPFs become more familiar with the requirements. Thus, we estimate 

that this policy will have a negligible impact on overall IPF payments for FY 2016. 
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Based on the proposals made in this rule, we estimate a total increase in burden of 174.4 

hours per IPF or 282,004.80 hours across all IPFs, resulting in a total increase in financial burden 

of $3,901.33 per IPF or $6,308,447.38 across all IPFs. As discussed in section VI. of this 

proposed rule, we will attribute the costs associated with the proposals to the year in which these 

costs begin; for the purposes of all the proposals in this proposed rule, that year is FY 

2016. Further information on these estimates can be found in section VI. of this proposed rule.

We intend to closely monitor the effects of this quality reporting program on IPFs and 

help facilitate successful reporting outcomes through ongoing stakeholder education, national 

trainings, and a technical help desk.

5. Effect on Beneficiaries

Under the IPF PPS, IPFs will receive payment based on the average resources consumed 

by patients for each day. We do not expect changes in the quality of care or access to services 

for Medicare beneficiaries under the FY 2016 IPF PPS, but we continue to expect that paying 

prospectively for IPF services would enhance the efficiency of the Medicare program. 

D. Alternatives Considered

The statute does not specify an update strategy for the IPF PPS and is broadly written to 

give the Secretary discretion in establishing an update methodology. Therefore, we are updating 

the IPF PPS using the methodology published in the November 2004 IPF PPS final rule, but with 

a proposed IPF-specific market basket, and updated labor-related share, a proposed transitional 

wage index to implement new OMB CBSA designations, and a proposed phase-out of the rural 

adjustment for the 37 providers changing from rural to urban status as a result of the updated 

OMB CBSA delineations used in the FY 2016 IPF PPS transitional wage index. We considered 

implementing the new OMB designations for the FY 2016 IPF PPS wage index without a blend, 
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but wanted to mitigate any negative effects of CBSA changes on IPFs. Additionally, we 

considered abruptly ending the rural adjustment for the 37 IPF providers which changed from 

rural to urban status as a result of the OMB CBSA changes. However, we wanted to propose 

relief from the effects of OMB’s new CBSA delineations to the 37 providers which changed 

from rural to urban status. We also considered whether to allow a phase-in of the updated LRS, 

but decided that the impact of full implementation did not warrant a phase-in, especially given 

that we also proposed a transitional wage index and a phase-out of the rural adjustment for those 

IPFs which changed status from rural to urban under the new CBSAs. Additionally, for the 

IPFQR Program, alternatives were not considered because the Program, as designed, best 

achieves quality reporting goals for the inpatient psychiatric care setting, while minimizing 

associated reporting burdens on IPFs. Section V. of this proposed rule discusses other benefits 

and objectives of the Program.

E. Accounting Statement

As required by OMB Circular A-4 (available at 

http://www.whitehouse.gov/omb/circulars_a004_a-4), in Table 27 below, we have prepared an 

accounting statement showing the classification of the expenditures associated with the 

provisions of this proposed rule. The costs for data submission presented in Table 27 are 

calculated in section VI, which also discusses the benefits of data collection. This table provides 

our best estimate of the increase in Medicare payments under the IPF PPS as a result of the 

changes presented in this proposed rule and based on the data for 1,617 IPFs in our database. 

Furthermore, we present the estimated costs associated with updating the IPFQR program. The 

increases in Medicare payments are classified as Federal transfers to IPF Medicare providers.
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 Table 27 —Accounting Statement: Classification of Estimated Expenditures

Change in Estimated Transfers from FY 2015 IPF PPS to FY 2016 IPF PPS:

Category Transfers

Annualized Monetized Transfers $80 million

From Whom to Whom? Federal Government to IPF Medicare 

Providers

FY 2016 Costs to Updating the Quality Reporting Program for IPFs:

Category Costs 

Annualized Monetized Costs for IPFs 

to Submit Data (Quality Reporting 

Program)

$6.31 million

In accordance with the provisions of Executive Order 12866, this proposed rule was 

reviewed by the Office of Management and Budget.
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List of Subjects in 42 CFR Part 412

Administrative practice and procedure, Health facilities, Medicare, Puerto Rico, Reporting and 

recordkeeping requirements.

For the reasons set forth in the preamble, the Centers for Medicare and Medicaid Services 

proposes to amend 42 CFR chapter IV as set forth below:

PART 412 –– PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL 

SERVICES

1. The authority citation for part 412 continues to read as follows:

AUTHORITY: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 

1395hh), sec. 124 of Pub. L. 106-113 (113 Stat. 1501A-332), sec. 1206 of Pub. L. 113-67, and 

sec. 112 of Pub. L. 113-93.

2. Section 412.428 is amended by revising paragraph (e) to read as follows:

§412.428 Publication of Updates to the inpatient psychiatric facility prospective payment 

system.

* * * * *

(e) Describe the ICD-10-CM coding changes and DRG classification changes discussed 

in the annual update to the hospital inpatient prospective payment system regulations.

* * * * *
CMS-1627-P

Dated: April 13, 2015.

______________________________

Andrew M. Slavitt,

Acting Administrator,

Centers for Medicare & Medicaid Services.

Approved: April 22, 2015.

______________________________

Sylvia M. Burwell,

Secretary.

BILLING CODE 4120-01-P
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NOTE: The following addendum will not publish in the Code of Federal Regulations.

Addendum—FY 2016 Proposed Rates and Adjustment Factors 

Per Diem Rate:

Federal Per Diem Base Rate $745.19

Labor Share (0.749) $558.15

Non-Labor Share (0.251) $187.04

Per Diem Rate Applying the 2 Percentage Point Reduction 

Federal Per Diem Base Rate $730.56

Labor Share (0.749) $547.19

Non-Labor Share (0.251) $183.37

Fixed Dollar Loss Threshold Amount:

$9,825

Wage Index Budget-Neutrality Factor:

1.0041

Facility Adjustments:

Rural Adjustment Factor 1.17

Teaching Adjustment Factor 0.5150

Wage Index Pre-reclass Hospital Wage Index (FY2015)
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Cost of Living Adjustments (COLAs):

Area

Cost of 

Living 

Adjustment 

Factor

Alaska:

City of Anchorage and 80-kilometer (50-mile) radius by road 1.23

City of Fairbanks and 80-kilometer (50-mile) radius by road 1.23

City of Juneau and 80-kilometer (50-mile) radius by road 1.23

Rest of Alaska 1.25

Hawaii:

City and County of Honolulu 1.25

County of Hawaii 1.19

County of Kauai 1.25

County of Maui and County of Kalawao 1.25

Patient Adjustments:

ECT – Per Treatment $320.82

ECT – Per Treatment Applying the 2 Percentage Point Reduction $314.52

Variable Per Diem Adjustments:

Adjustment Factor

Day 1 -- Facility Without a Qualifying Emergency Department 1.19

Day 1 -- Facility With a Qualifying Emergency Department 1.31

Day 2 1.12

Day 3 1.08

Day 4 1.05

Day 5 1.04

Day 6 1.02

Day 7 1.01

Day 8 1.01

Day 9 1.00

Day 10 1.00

Day 11 0.99

Day 12 0.99

Day 13 0.99

Day 14 0.99

Day 15 0.98

Day 16 0.97

Day 17 0.97

Day 18 0.96

Day 19 0.95
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Adjustment Factor

Day 20 0.95

Day 21 0.95

After Day 21 0.92

Age Adjustments:

Age (in years) Adjustment Factor

Under 45 1.00

45 and under 50 1.01

50 and under 55 1.02

55 and under 60 1.04

60 and under 65 1.07

65 and under 70 1.10

70 and under 75 1.13

75 and under 80 1.15

80 and over 1.17

DRG Adjustments:

MS-DRG MS-DRG Descriptions

Adjustment 

Factor

056

057

Degenerative nervous system disorders w MCC

Degenerative nervous system disorders w/o MCC

1.05

080

081

Nontraumatic stupor & coma w MCC

Nontraumatic stupor & coma w/o MCC

1.07

876 O.R. procedure w principal diagnoses of mental illness 1.22

880 Acute adjustment reaction & psychosocial dysfunction 1.05

881 Depressive neuroses 0.99

882 Neuroses except depressive 1.02

883 Disorders of personality & impulse control 1.02

884 Organic disturbances & mental retardation 1.03

885 Psychoses 1.00

886 Behavioral & developmental disorders 0.99

887 Other mental disorder diagnoses 0.92

894 Alcohol/drug abuse or dependence, left AMA 0.97

895 Alcohol/drug abuse or dependence w rehabilitation therapy 1.02

896

897

Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC

Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC

0.88

Comorbidity Adjustments:

Comorbidity

Adjustment 

Factor

Developmental Disabilities 1.04

Coagulation Factor Deficit 1.13

Tracheostomy 1.06

Eating and Conduct Disorders 1.12
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Comorbidity

Adjustment 

Factor

Infectious Diseases 1.07

Renal Failure, Acute 1.11

Renal Failure, Chronic 1.11

Oncology Treatment 1.07

Uncontrolled Diabetes Mellitus 1.05

Severe Protein Malnutrition 1.13

Drug/Alcohol Induced Mental Disorders 1.03

Cardiac Conditions 1.11

Gangrene 1.10

Chronic Obstructive Pulmonary Disease 1.12

Artificial Openings – Digestive & Urinary 1.08

Severe Musculoskeletal & Connective Tissue Diseases 1.09

Poisoning 1.11